Using the optical mouse sensor as a two-euro counterfeit coin detector

In this paper, the sensor of an optical mouse is presented as a counterfeit coin detector applied to the two-Euro case. The detection process is based on the short distance image acquisition capabilities of the optical mouse sensor where partial images of the coin under analysis are compared with some partial reference coin images for matching. Results show that, using only the vision sense, the counterfeit acceptance and rejection rates are very similar to those of a trained user and better than those of an untrained user.

Automated monitoring of medical protocols: a secure and distributed architecture

The control of the right application of medical protocols is a key issue in hospital environments. For the automated monitoring of medical protocols, we need a domain-independent language for their representation and a fully, or semi, autonomous system that understands the protocols and supervises their application. In this paper we describe a specification language and a multi-agent system architecture for monitoring medical protocols. We model medical services in hospital environments as specialized domain agents and interpret a medical protocol as a negotiation process between agents. A medical service can be involved in multiple medical protocols, and so specialized domain agents are independent of negotiation processes and autonomous system agents perform monitoring tasks. We present the detailed architecture of the system agents and of an important domain agent, the database broker agent, that is responsible of obtaining relevant information about the clinical history of patients. We also describe how we tackle the problems of privacy, integrity and authentication during the process of exchanging information between agents.

Time patterns and perceptions of online learning success factors

Online learning provides the opportunity to work on academic tasks at any time at the same time as doing other activities, such as using in web 2.0 tools. This study identifies factors that contribute to success in online learning from the students¿ perspective and their relationship with time patterns. A survey of learning outputs was used to find relationships between students¿ satisfaction, knowledge acquisition and knowledge transfer with time for working on academic tasks. In this study, 199 students from a university in Mexico completed the survey. Findings suggest that knowledge transfer has a significant association with the number of hours online per day, hours spent on social networks and the use made of e-learning during working hours. Learner satisfaction has a strong relationship with the time in years a learner has been using the Internet and the number of hours devoted to the course per week. The findings of this research will be helpful for faculty and instructional designers for implementing learning strategies.

NADPH oxidase NOX4 mediates stellate cell activation and hepatocyte cell death during liver fibrosis development.

A role for the NADPH oxidases NOX1 and NOX2 in liver fibrosis has been proposed, but the implication of NOX4 is poorly understood yet. The aim of this work was to study the functional role of NOX4 in different cell populations implicated in liver fibrosis: hepatic stellate cells (HSC), myofibroblats (MFBs) and hepatocytes. Two different mice models that develop spontaneous fibrosis (Mdr2−/−/p19ARF−/−, Stat3Δhc/Mdr2−/−) and a model of experimental induced fibrosis (CCl4) were used. In addition, gene expression in biopsies from chronic hepatitis C virus (HCV) patients or non-fibrotic liver samples was analyzed. Results have indicated that NOX4 expression was increased in the livers of all animal models, concomitantly with fibrosis development and TGF-β pathway activation. In vitro TGF-β-treated HSC increased NOX4 expression correlating with transdifferentiation to MFBs. Knockdown experiments revealed that NOX4 downstream TGF-β is necessary for HSC activation as well as for the maintenance of the MFB phenotype. NOX4 was not necessary for TGF-β-induced epithelial-mesenchymal transition (EMT), but was required for TGF-β-induced apoptosis in hepatocytes. Finally, NOX4 expression was elevated in patients with hepatitis C virus (HCV)-derived fibrosis, increasing along the fibrosis degree. In summary, fibrosis progression both in vitro and in vivo (animal models and patients) is accompanied by increased NOX4 expression, which mediates acquisition and maintenance of the MFB phenotype, as well as TGF-β-induced death of hepatocytes.

Lossless Compression Methods for Multispectral Images: Development and Comparisons

Main purpose of this thesis is to introduce a new lossless compression algorithm for multispectral images. Proposed algorithm is based on reducing the band ordering problem to the problem of finding a minimum spanning tree in a weighted directed graph, where set of the graph vertices corresponds to multispectral image bands and the arcs’ weights have been computed using a newly invented adaptive linear prediction model. The adaptive prediction model is an extended unification of 2–and 4–neighbour pixel context linear prediction schemes. The algorithm provides individual prediction of each image band using the optimal prediction scheme, defined by the adaptive prediction model and the optimal predicting band suggested by minimum spanning tree. Its efficiency has been compared with respect to the best lossless compression algorithms for multispectral images. Three recently invented algorithms have been considered. Numerical results produced by these algorithms allow concluding that adaptive prediction based algorithm is the best one for lossless compression of multispectral images. Real multispectral data captured from an airplane have been used for the testing.

Development of cardiovascular magnetic resonance imaging techniques for improved characterization of atherosclerotic disease

Atherosclerosis is a chronic cardiovascular disease that involves the thicken¬ing of the artery walls as well as the formation of plaques (lesions) causing the narrowing of the lumens, in vessels such as the aorta, the coronary and the carotid arteries. Magnetic resonance imaging (MRI) is a promising modality for the assessment of atherosclerosis, as it is a non-invasive and patient-friendly procedure that does not use ionizing radiation. MRI offers high soft tissue con¬trast already without the need of intravenous contrast media; while modifica¬tion of the MR pulse sequences allows for further adjustment of the contrast for specific diagnostic needs. As such, MRI can create angiographic images of the vessel lumens to assess stenoses at the late stage of the disease, as well as blood flow-suppressed images for the early investigation of the vessel wall and the characterization of the atherosclerotic plaques. However, despite the great technical progress that occurred over the past two decades, MRI is intrinsically a low sensitive technique and some limitations still exist in terms of accuracy and performance. A major challenge for coronary artery imaging is respiratory motion. State- of-the-art diaphragmatic navigators rely on an indirect measure of motion, per¬form a ID correction, and have long and unpredictable scan time. In response, self-navigation (SM) strategies have recently been introduced that offer 100% scan efficiency and increased ease of use. SN detects respiratory motion di¬rectly from the image data obtained at the level of the heart, and retrospectively corrects the same data before final image reconstruction. Thus, SN holds po-tential for multi-dimensional motion compensation. To this regard, this thesis presents novel SN methods that estimate 2D and 3D motion parameters from aliased sub-images that are obtained from the same raw data composing the final image. Combination of all corrected sub-images produces a final image with reduced motion artifacts for the visualization of the coronaries. The first study (section 2.2, 2D Self-Navigation with Compressed Sensing) consists of a method for 2D translational motion compensation. Here, the use of com- pressed sensing (CS) reconstruction is proposed and investigated to support motion detection by reducing aliasing artifacts. In healthy human subjects, CS demonstrated an improvement in motion detection accuracy with simula¬tions on in vivo data, while improved coronary artery visualization was demon¬strated on in vivo free-breathing acquisitions. However, the motion of the heart induced by respiration has been shown to occur in three dimensions and to be more complex than a simple translation. Therefore, the second study (section 2.3,3D Self-Navigation) consists of a method for 3D affine motion correction rather than 2D only. Here, different techniques were adopted to reduce background signal contribution in respiratory motion tracking, as this can be adversely affected by the static tissue that surrounds the heart. The proposed method demonstrated to improve conspicuity and vi¬sualization of coronary arteries in healthy and cardiovascular disease patient cohorts in comparison to a conventional ID SN method. In the third study (section 2.4, 3D Self-Navigation with Compressed Sensing), the same tracking methods were used to obtain sub-images sorted according to the respiratory position. Then, instead of motion correction, a compressed sensing reconstruction was performed on all sorted sub-image data. This process ex¬ploits the consistency of the sorted data to reduce aliasing artifacts such that the sub-image corresponding to the end-expiratory phase can directly be used to visualize the coronaries. In a healthy volunteer cohort, this strategy improved conspicuity and visualization of the coronary arteries when compared to a con¬ventional ID SN method. For the visualization of the vessel wall and atherosclerotic plaques, the state- of-the-art dual inversion recovery (DIR) technique is able to suppress the signal coming from flowing blood and provide positive wall-lumen contrast. How¬ever, optimal contrast may be difficult to obtain and is subject to RR variability. Furthermore, DIR imaging is time-inefficient and multislice acquisitions may lead to prolonged scanning times. In response and as a fourth study of this thesis (chapter 3, Vessel Wall MRI of the Carotid Arteries), a phase-sensitive DIR method has been implemented and tested in the carotid arteries of a healthy volunteer cohort. By exploiting the phase information of images acquired after DIR, the proposed phase-sensitive method enhances wall-lumen contrast while widens the window of opportunity for image acquisition. As a result, a 3-fold increase in volumetric coverage is obtained at no extra cost in scanning time, while image quality is improved. In conclusion, this thesis presented novel methods to address some of the main challenges for MRI of atherosclerosis: the suppression of motion and flow artifacts for improved visualization of vessel lumens, walls and plaques. Such methods showed to significantly improve image quality in human healthy sub¬jects, as well as scan efficiency and ease-of-use of MRI. Extensive validation is now warranted in patient populations to ascertain their diagnostic perfor¬mance. Eventually, these methods may bring the use of atherosclerosis MRI closer to the clinical practice. Résumé L'athérosclérose est une maladie cardiovasculaire chronique qui implique le épaississement de la paroi des artères, ainsi que la formation de plaques (lé¬sions) provoquant le rétrécissement des lumières, dans des vaisseaux tels que l'aorte, les coronaires et les artères carotides. L'imagerie par résonance magné¬tique (IRM) est une modalité prometteuse pour l'évaluation de l'athérosclérose, car il s'agit d'une procédure non-invasive et conviviale pour les patients, qui n'utilise pas des rayonnements ionisants. L'IRM offre un contraste des tissus mous très élevé sans avoir besoin de médias de contraste intraveineux, tan¬dis que la modification des séquences d'impulsions de RM permet en outre le réglage du contraste pour des besoins diagnostiques spécifiques. À ce titre, l'IRM peut créer des images angiographiques des lumières des vaisseaux pour évaluer les sténoses à la fin du stade de la maladie, ainsi que des images avec suppression du flux sanguin pour une première enquête des parois des vais¬seaux et une caractérisation des plaques d'athérosclérose. Cependant, malgré les grands progrès techniques qui ont eu lieu au cours des deux dernières dé¬cennies, l'IRM est une technique peu sensible et certaines limitations existent encore en termes de précision et de performance. Un des principaux défis pour l'imagerie de l'artère coronaire est le mou¬vement respiratoire. Les navigateurs diaphragmatiques de pointe comptent sur une mesure indirecte de mouvement, effectuent une correction 1D, et ont un temps d'acquisition long et imprévisible. En réponse, les stratégies d'auto- navigation (self-navigation: SN) ont été introduites récemment et offrent 100% d'efficacité d'acquisition et une meilleure facilité d'utilisation. Les SN détectent le mouvement respiratoire directement à partir des données brutes de l'image obtenue au niveau du coeur, et rétrospectivement corrigent ces mêmes données avant la reconstruction finale de l'image. Ainsi, les SN détiennent un poten¬tiel pour une compensation multidimensionnelle du mouvement. A cet égard, cette thèse présente de nouvelles méthodes SN qui estiment les paramètres de mouvement 2D et 3D à partir de sous-images qui sont obtenues à partir des mêmes données brutes qui composent l'image finale. La combinaison de toutes les sous-images corrigées produit une image finale pour la visualisation des coronaires ou les artefacts du mouvement sont réduits. La première étude (section 2.2,2D Self-Navigation with Compressed Sensing) traite d'une méthode pour une compensation 2D de mouvement de translation. Ici, on étudie l'utilisation de la reconstruction d'acquisition comprimée (compressed sensing: CS) pour soutenir la détection de mouvement en réduisant les artefacts de sous-échantillonnage. Chez des sujets humains sains, CS a démontré une amélioration de la précision de la détection de mouvement avec des simula¬tions sur des données in vivo, tandis que la visualisation de l'artère coronaire sur des acquisitions de respiration libre in vivo a aussi été améliorée. Pourtant, le mouvement du coeur induite par la respiration se produit en trois dimensions et il est plus complexe qu'un simple déplacement. Par conséquent, la deuxième étude (section 2.3, 3D Self-Navigation) traite d'une méthode de cor¬rection du mouvement 3D plutôt que 2D uniquement. Ici, différentes tech¬niques ont été adoptées pour réduire la contribution du signal du fond dans le suivi de mouvement respiratoire, qui peut être influencé négativement par le tissu statique qui entoure le coeur. La méthode proposée a démontré une amélioration, par rapport à la procédure classique SN de correction 1D, de la visualisation des artères coronaires dans le groupe de sujets sains et des pa¬tients avec maladies cardio-vasculaires. Dans la troisième étude (section 2.4,3D Self-Navigation with Compressed Sensing), les mêmes méthodes de suivi ont été utilisées pour obtenir des sous-images triées selon la position respiratoire. Au lieu de la correction du mouvement, une reconstruction de CS a été réalisée sur toutes les sous-images triées. Cette procédure exploite la cohérence des données pour réduire les artefacts de sous- échantillonnage de telle sorte que la sous-image correspondant à la phase de fin d'expiration peut directement être utilisée pour visualiser les coronaires. Dans un échantillon de volontaires en bonne santé, cette stratégie a amélioré la netteté et la visualisation des artères coronaires par rapport à une méthode classique SN ID. Pour la visualisation des parois des vaisseaux et de plaques d'athérosclérose, la technique de pointe avec double récupération d'inversion (DIR) est capa¬ble de supprimer le signal provenant du sang et de fournir un contraste posi¬tif entre la paroi et la lumière. Pourtant, il est difficile d'obtenir un contraste optimal car cela est soumis à la variabilité du rythme cardiaque. Par ailleurs, l'imagerie DIR est inefficace du point de vue du temps et les acquisitions "mul- tislice" peuvent conduire à des temps de scan prolongés. En réponse à ce prob¬lème et comme quatrième étude de cette thèse (chapitre 3, Vessel Wall MRI of the Carotid Arteries), une méthode de DIR phase-sensitive a été implémenté et testé

Candida albicans Inhibits Pseudomonas aeruginosa Virulence through Suppression of Pyochelin and Pyoverdine Biosynthesis.

Bacterial-fungal interactions have important physiologic and medical ramifications, but the mechanisms of these interactions are poorly understood. The gut is host to trillions of microorganisms, and bacterial-fungal interactions are likely to be important. Using a neutropenic mouse model of microbial gastrointestinal colonization and dissemination, we show that the fungus Candida albicans inhibits the virulence of the bacterium Pseudomonas aeruginosa by inhibiting P. aeruginosa pyochelin and pyoverdine gene expression, which plays a critical role in iron acquisition and virulence. Accordingly, deletion of both P. aeruginosa pyochelin and pyoverdine genes attenuates P. aeruginosa virulence. Heat-killed C. albicans has no effect on P. aeruginosa, whereas C. albicans secreted proteins directly suppress P. aeruginosa pyoverdine and pyochelin expression and inhibit P. aeruginosa virulence in mice. Interestingly, suppression or deletion of pyochelin and pyoverdine genes has no effect on P. aeruginosa's ability to colonize the GI tract but does decrease P. aeruginosa's cytotoxic effect on cultured colonocytes. Finally, oral iron supplementation restores P. aeruginosa virulence in P. aeruginosa and C. albicans colonized mice. Together, our findings provide insight into how a bacterial-fungal interaction can modulate bacterial virulence in the intestine. Previously described bacterial-fungal antagonistic interactions have focused on growth inhibition or colonization inhibition/modulation, yet here we describe a novel observation of fungal-inhibition of bacterial effectors critical for virulence but not important for colonization. These findings validate the use of a mammalian model system to explore the complexities of polymicrobial, polykingdom infections in order to identify new therapeutic targets for preventing microbial disease.

Body Image in Eating Disorders: The Influence of Exposure to Virtual-Reality Environments.

The aim of this article was to study the effect of virtual-reality exposure to situations that are emotionally significant for patients with eating disorders (ED) on the stability of body-image distortion and body-image dissatisfaction. A total of 85 ED patients and 108 non-ED students were randomly exposed to four experimental virtual environments: a kitchen with low-calorie food, a kitchen with high-calorie food, a restaurant with low-calorie food, and a restaurant with high-calorie food. In the interval between the presentation of each situation, body-image distortion and body-image dissatisfaction were assessed. Several 2 x 2 x 2 repeated measures analyses of variance (high-calorie vs. low-calorie food x presence vs. absence of people x ED group vs. control group) showed that ED participants had significantly higher levels of body-image distortion and body dissatisfaction after eating high-calorie food than after eating low-calorie food, while control participants reported a similar body image in all situations. The results suggest that body-image distortion and body-image dissatisfaction show both trait and state features. On the one hand, ED patients show a general predisposition to overestimate their body size and to feel more dissatisfied with their body image than controls. On the other hand, these body-image disturbances fluctuate when participants are exposed to virtual situations that are emotionally relevant for them.

Immune correlates of vaccine protection against HIV-1 acquisition.

The partial efficacy reported in the RV144 HIV vaccine trial in 2009 has driven the HIV vaccine field to define correlates of risk associated with HIV-1 acquisition and connect these functionally to preventing HIV infection. Immunological correlates, mainly including CD4(+) T cell responses to the HIV envelope and Fc-mediated antibody effector function, have been connected to reduced acquisition. These immunological correlates place immunological and genetic pressure on the virus. Indeed, antibodies directed at conserved regions of the V1V2 loop and antibodies that mediate antibody-dependent cellular cytotoxicity to HIV envelope in the absence of inhibiting serum immunoglobulin A antibodies correlated with decreased HIV risk. More recently, researchers have expanded their search with nonhuman primate studies using vaccine regimens that differ from that used in RV144; these studies indicate that non-neutralizing antibodies are associated with protection from experimental lentivirus challenge as well. These immunological correlates have provided the basis for the design of a next generation of vaccine regimens to improve upon the qualitative and quantitative degree of magnitude of these immune responses on HIV acquisition.

Image quality in CT: From physical measurements to model observers.

Evaluation of image quality (IQ) in Computed Tomography (CT) is important to ensure that diagnostic questions are correctly answered, whilst keeping radiation dose to the patient as low as is reasonably possible. The assessment of individual aspects of IQ is already a key component of routine quality control of medical x-ray devices. These values together with standard dose indicators can be used to give rise to 'figures of merit' (FOM) to characterise the dose efficiency of the CT scanners operating in certain modes. The demand for clinically relevant IQ characterisation has naturally increased with the development of CT technology (detectors efficiency, image reconstruction and processing), resulting in the adaptation and evolution of assessment methods. The purpose of this review is to present the spectrum of various methods that have been used to characterise image quality in CT: from objective measurements of physical parameters to clinically task-based approaches (i.e. model observer (MO) approach) including pure human observer approach. When combined together with a dose indicator, a generalised dose efficiency index can be explored in a framework of system and patient dose optimisation. We will focus on the IQ methodologies that are required for dealing with standard reconstruction, but also for iterative reconstruction algorithms. With this concept the previously used FOM will be presented with a proposal to update them in order to make them relevant and up to date with technological progress. The MO that objectively assesses IQ for clinically relevant tasks represents the most promising method in terms of radiologist sensitivity performance and therefore of most relevance in the clinical environment.

Corporate Social and Regional Responsibility - The View of Small and Medium-sized Enterprises

The objective of this research was to understand and describe what corpo-rate social and regional responsibility is in SMEs and define the meaning of these concepts to the community and region. Corporate social respon-sibility (CSR) creates a basis for regional responsibility. Regional respon-sibility is a new concept and this research examines it from SMEs’ view-point. This is a theoretical research and the aim is to create a theoretical framework of SMEs’ corporate social and regional responsibility. This framework supports the future research on the subject. The research results show that CSR of SMEs is practical, informal and dependent on the scarce resources of SMEs. CSR is a complex and deep concept and SMEs have their own way of interpreting it. It can be stated that CSR-practises in SMEs are closely connected to employment, envi-ronment, community and supply chain. The challenge is to find motivation to socially and regionally responsible behaviour in SMEs. Benefiting from responsible behaviour and the attitude of SME’s owner-manager are the key reasons for SMEs to involve in CSR and regional responsibility. The benefits of this involvement are for example improved image, reputation and market position. CSR can also be used in SMEs as risk management tool and in cost reduction. This study indicates also that creation of strate-gic partnerships, local government participation, a proper legal system and financial support are the basic issues which support CSR of SMEs. This research showed that regional responsibility of SMEs includes active participation in regional strategy processes, L&RED initiatives and regional philanthropy. For SMEs regional responsibility means good relationships with the community and other related stakeholders, involvement in L&RED initiatives and acting responsibly towards the operating environment. In SMEs’ case this means that they need to understand the benefits of this kind of involvement in order to take action and participate. As regional responsibility includes the relationships between firm and the community, it can be stated that regional responsibility extends CSR’s view of stakeholders and emphasises both, the regional stakeholders and public-private partnerships. Community engagement and responsible be-haviour towards community can be seen as a part of SMEs’ social and regional responsibility. This study indicates that social and regional re-sponsibility of SMEs have a significant influence on the community and region where they are located. Better local and regional relationships with regional and community actors are the positive impacts of social and re-gional responsibility of SMEs. Socially and regionally responsible behav-iour creates a more positive environment and deepens the involvement of SMEs to community and L&RED initiatives.

From breaking the rule to making the rules : the adoption, entrenchment and diffusion of gender quotas in France

Once a country allergic to any type of preferential treatment or quota measure for women, France has become a country that applies gender quotas to regulate women's presence and representation in politics, the business sector, public bodies, public administration, and even some civil society organizations. While research has concentrated on the adoption of electoral gender quotas in many countries and their international diffusion, few studies focus on explaining the successful diffusion of gender quotas from politics to other domains in the same country. This paper proposes to fill this gap by studying the particularly puzzling case of a country that at one point strongly opposed the adoption of gender quotas in politics, but, in less than a decade, transformed into one of the few countries applying gender quotas across several policy domains. This paper argues that the legal entrenchment of the parity principle, the institutionalization of parity in several successive women's policy agencies, and key players in these newly created agencies are mainly responsible for this unexpected development. The diffusion of gender quotas in France thus offers an illuminating example of under which conditions women's policy agencies can act autonomously to diffuse and impose a new tool for gender equality

Semantic domain and grammatical class effects in the picture-word interference paradigm

The role of grammatical class in lexical access and representation is still not well understood. Grammatical effects obtained in picture-word interference experiments have been argued to show the operation of grammatical constraints during lexicalization when syntactic integration is required by the task. Alternative views hold that the ostensibly grammatical effects actually derive from the coincidence of semantic and grammatical differences between lexical candidates. We present three picture-word interference experiments conducted in Spanish. In the first two, the semantic relatedness (related or unrelated) and the grammatical class (nouns or verbs) of the target and the distracter were manipulated in an infinitive form action naming task in order to disentangle their contributions to verb lexical access. In the third experiment, a possible confound between grammatical class and semantic domain (objects or actions) was eliminated by using action-nouns as distracters. A condition in which participants were asked to name the action pictures using an inflected form of the verb was also included to explore whether the need of syntactic integration modulated the appearance of grammatical effects. Whereas action-words (nouns or verbs), but not object-nouns, produced longer reaction times irrespective of their grammatical class in the infinitive condition, only verbs slowed latencies in the inflected form condition. Our results suggest that speech production relies on the exclusion of candidate responses that do not fulfil task-pertinent criteria like membership in the appropriate semantic domain or grammatical class. Taken together, these findings are explained by a response-exclusion account of speech output. This and alternative hypotheses are discussed.

Feature-based matching of underwater images

This work investigates performance of recent feature-based matching techniques when applied to registration of underwater images. Matching methods are tested versus different contrast enhancing pre-processing of images. As a result of the performed experiments for various dominating in images underwater artifacts and present deformation, the outperforming preprocessing, detection and description methods are proposed

New Distance Transforms for Gray Level Image Compression

This thesis deals with distance transforms which are a fundamental issue in image processing and computer vision. In this thesis, two new distance transforms for gray level images are presented. As a new application for distance transforms, they are applied to gray level image compression. The new distance transforms are both new extensions of the well known distance transform algorithm developed by Rosenfeld, Pfaltz and Lay. With some modification their algorithm which calculates a distance transform on binary images with a chosen kernel has been made to calculate a chessboard like distance transform with integer numbers (DTOCS) and a real value distance transform (EDTOCS) on gray level images. Both distance transforms, the DTOCS and EDTOCS, require only two passes over the graylevel image and are extremely simple to implement. Only two image buffers are needed: The original gray level image and the binary image which defines the region(s) of calculation. No other image buffers are needed even if more than one iteration round is performed. For large neighborhoods and complicated images the two pass distance algorithm has to be applied to the image more than once, typically 3 10 times. Different types of kernels can be adopted. It is important to notice that no other existing transform calculates the same kind of distance map as the DTOCS. All the other gray weighted distance function, GRAYMAT etc. algorithms find the minimum path joining two points by the smallest sum of gray levels or weighting the distance values directly by the gray levels in some manner. The DTOCS does not weight them that way. The DTOCS gives a weighted version of the chessboard distance map. The weights are not constant, but gray value differences of the original image. The difference between the DTOCS map and other distance transforms for gray level images is shown. The difference between the DTOCS and EDTOCS is that the EDTOCS calculates these gray level differences in a different way. It propagates local Euclidean distances inside a kernel. Analytical derivations of some results concerning the DTOCS and the EDTOCS are presented. Commonly distance transforms are used for feature extraction in pattern recognition and learning. Their use in image compression is very rare. This thesis introduces a new application area for distance transforms. Three new image compression algorithms based on the DTOCS and one based on the EDTOCS are presented. Control points, i.e. points that are considered fundamental for the reconstruction of the image, are selected from the gray level image using the DTOCS and the EDTOCS. The first group of methods select the maximas of the distance image to new control points and the second group of methods compare the DTOCS distance to binary image chessboard distance. The effect of applying threshold masks of different sizes along the threshold boundaries is studied. The time complexity of the compression algorithms is analyzed both analytically and experimentally. It is shown that the time complexity of the algorithms is independent of the number of control points, i.e. the compression ratio. Also a new morphological image decompression scheme is presented, the 8 kernels' method. Several decompressed images are presented. The best results are obtained using the Delaunay triangulation. The obtained image quality equals that of the DCT images with a 4 x 4