Active regions for colour texture segmentation integrating region and boundary information

In this paper a colour texture segmentation method, which unifies region and boundary information, is proposed. The algorithm uses a coarse detection of the perceptual (colour and texture) edges of the image to adequately place and initialise a set of active regions. Colour texture of regions is modelled by the conjunction of non-parametric techniques of kernel density estimation (which allow to estimate the colour behaviour) and classical co-occurrence matrix based texture features. Therefore, region information is defined and accurate boundary information can be extracted to guide the segmentation process. Regions concurrently compete for the image pixels in order to segment the whole image taking both information sources into account. Furthermore, experimental results are shown which prove the performance of the proposed method

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

Analysis of Satellite Data for Forest Segmentation

In this work we study the classification of forest types using mathematics based image analysis on satellite data. We are interested in improving classification of forest segments when a combination of information from two or more different satellites is used. The experimental part is based on real satellite data originating from Canada. This thesis gives summary of the mathematics basics of the image analysis and supervised learning , methods that are used in the classification algorithm. Three data sets and four feature sets were investigated in this thesis. The considered feature sets were 1) histograms (quantiles) 2) variance 3) skewness and 4) kurtosis. Good overall performances were achieved when a combination of ASTERBAND and RADARSAT2 data sets was used.

Color ad spectral image assessment using novel quality and fidelity techniques

The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.

Comparison Structure Analysis

This study presents an automatic, computer-aided analytical method called Comparison Structure Analysis (CSA), which can be applied to different dimensions of music. The aim of CSA is first and foremost practical: to produce dynamic and understandable representations of musical properties by evaluating the prevalence of a chosen musical data structure through a musical piece. Such a comparison structure may refer to a mathematical vector, a set, a matrix or another type of data structure and even a combination of data structures. CSA depends on an abstract systematic segmentation that allows for a statistical or mathematical survey of the data. To choose a comparison structure is to tune the apparatus to be sensitive to an exclusive set of musical properties. CSA settles somewhere between traditional music analysis and computer aided music information retrieval (MIR). Theoretically defined musical entities, such as pitch-class sets, set-classes and particular rhythm patterns are detected in compositions using pattern extraction and pattern comparison algorithms that are typical within the field of MIR. In principle, the idea of comparison structure analysis can be applied to any time-series type data and, in the music analytical context, to polyphonic as well as homophonic music. Tonal trends, set-class similarities, invertible counterpoints, voice-leading similarities, short-term modulations, rhythmic similarities and multiparametric changes in musical texture were studied. Since CSA allows for a highly accurate classification of compositions, its methods may be applicable to symbolic music information retrieval as well. The strength of CSA relies especially on the possibility to make comparisons between the observations concerning different musical parameters and to combine it with statistical and perhaps other music analytical methods. The results of CSA are dependent on the competence of the similarity measure. New similarity measures for tonal stability, rhythmic and set-class similarity measurements were proposed. The most advanced results were attained by employing the automated function generation – comparable with the so-called genetic programming – to search for an optimal model for set-class similarity measurements. However, the results of CSA seem to agree strongly, independent of the type of similarity function employed in the analysis.

A Technique for Digital Color Image Watermarking Using ICA

With the increase of use of digital media the need for the methods of multimedia protection becomes extremely important. The number of the solutions to the problem from encryption to watermarking is large and is growing every year. In this work digital image watermarking is considered, specifically a novel method of digital watermarking of color and spectral images. An overview of existing methods watermarking of color and grayscale images is given in the paper. Methods using independent component analysis (ICA) for detection and the ones using discrete wavelet transform (DWT) and discrete cosine transform (DCT) are considered in more detail. A novel method of watermarking proposed in this paper allows embedding of a color or spectral watermark image into color or spectral image consequently and successful extraction of the watermark out of the resultant watermarked image. A number of experiments have been performed on the quality of extraction depending on the parameters of the embedding procedure. Another set of experiments included the test of the robustness of the algorithm proposed. Three techniques have been chosen for that purpose: median filter, low-pass filter (LPF) and discrete cosine transform (DCT), which are a part of a widely known StirMark - Image Watermarking Robustness Test. The study shows that the proposed watermarking technique is fragile, i.e. watermark is altered by simple image processing operations. Moreover, we have found that the contents of the image to be watermarked do not affect the quality of the extraction. Mixing coefficients, that determine the amount of the key and watermark image in the result, should not exceed 1% of the original. The algorithm proposed has proven to be successful in the task of watermark embedding and extraction.

Analysis of land use and occupancy in permanent preservation areas according to the hydrography of Ribeirão Água Fria - Bofete, SP - Brazil

The use conflicts are determined by the inadequate occupations of the soil, as it is the case of soil occupation inside of permanent preservation areas. This study aimed to determine the classes of the soil use and if there are conflicts inside of permanent preservation areas along the drainage network of the Água Fria Stream watershed, located in Bofete city - São Paulo, Brazil. It locates geographically between the coordinates: 48°09'30" to 48°18'30" longitude WGr., 22°58'30" to 23°04'30" latitude S, with an area of 15242.84 ha. The map of soil use was elaborated through the interpretation directly in the computer screen of satellite digital image. In the orbital data, the study area is inserted in the quadrant A, of image TM/Landsat - 5, orbit 220, point 76, passage 9/8th/2007. The Geographical Information System used was CartaLinx. The conflict areas of the watershed were obtained from the crossing between the maps of soil use and of PPAs. The results allowed the conclusion that more than half of the area (51.09%) is occupied by pastures, reflex of sandy soils and low fertility. It was also verified that although almost half of the watershed is covered with some type of vegetation (48.78% of natural forest /reforestation), it has approximately a third of permanent preservation areas used inappropriately by pastures (88.15%), reforestation (10.42%) and exposed soil (1.43%), totaling 343.07ha of conflicting areas, in a total of 993.26 ha of PPAs.

Effect of companion ion on nitrate displacement through transport parameters analysis

Nitrate is the main form of nitrogen associated with water contamination; the high mobility of this species in soil justifies the concern regarding nitrogen management in agricultural soils. Therefore, the objective of this research was to assess the effect of companion cation on nitrate displacement, by analyzing nitrate transport parameters through Breakthrough Curves (BTCs) and their settings made by numerical model (STANMOD). The experiment was carried out in the Soil and Water Quality Laboratory of the Department of Biosystems Engineering, "Luiz de Queiroz" College of Agriculture in Piracicaba (SP), Brazil. It was performed using saturated soil columns in steady-state flow condition, in which two different sources of inorganic nitrate Ca(NO3)2 and NH4NO3 were applied at a concentration of 50 mg L-1 NO3-. Each column was filled with either a Red-Yellow Oxisol (S1) or an Alfisol (S2). Results are indicative that the companion ion had no effect on nitrate displacement. However, nitrate transport was influenced by soil texture, particle aggregation, solution speed in soil and organic matter presence. Nitrate mobility was higher in the Alfisol (S2).

Application of morphometry, static DNA ploidy analysis, and steroid receptor expression in diagnosis and prognosis of Libyan breast cancer

The aim of this study was to describe the demographic, clinicopathological, biological and morphometric features of Libyan breast cancer patients. The supporting value of nuclear morphometry and static image cytometry in the sensitivity for detecting breast cancer in conventional fine-needle aspiration biopsies were estimated. The findings were compared with findings in breast cancer in Finland and Nigeria. In addation, the value of ER and PR were evaluated. There were 131 histological samples, 41 cytological samples, and demographic and clinicopathological data from 234 Libyan patients. The Libyan breast cancer is dominantly premenopausal and in this feature it is similar to breast cancer in sub-Saharan Africans, but clearly different from breast cancer in Europeans, whose cancers are dominantly postmenopausal in character. At presention most Libyan patients have locally advanced disease, which is associated with poor survival rates. Nuclear morphometry and image DNA cytometry agree with earlier published data in the Finnish population and indicate that nuclear size and DNA analysis of nuclear content can be used to increase the cytological sensitivity and specificity in doubtful breast lesions, particularly when free cell sampling method is used. Combination of the morphometric data with earlier free cell data gave the following diagnostic guidelines: Range of overlap in free cell samples: 55 μm2 -71 μm2. Cut-off values for diagnostic purposes: Mean nuclear area (MNA) >54 μm2 for 100% detection of malignant cases (specificity 84 %), MNA < 72 μm2 for 100% detection of benign cases (sensitivity 91%). Histomorphometry showed a significant correlation between the MNA and most clinicopathological features, with the strongest association observed for histological grade (p <0.0001). MNA seems to be a prognosticator in Libyan breast cancer (Pearson’s test r = - 0.29, p = 0.019), but at lower level of significance than in the European material. A corresponding relationship was not found in shape-related morphometric features. ER and PR staining scores were in correlation with the clinical stage (p= 0.017, and 0.015, respectively), and also associated with lymph node negative patients (p=0.03, p=0.05, respectively). Receptor-positive (HR+) patients had a better survival. The fraction of HR+ cases among Libyan breast cancers is about the same as the fraction of positive cases in European breast cancer. The study suggests that also weak staining (corresponding to as few as 1% positive cells) has prognostic value. The prognostic significance may be associated with the practice to use antihormonal therapy in HR+ cases. The low survival and advanced presentation is associated with active cell proliferation, atypical nuclear morphology and aneuploid nuclear DNA content in Libyan breast cancer patients. The findings support the idea that breast cancer is not one type of disease, but should probably be classified into premenopausal and post menopausal types.

Analysis of natural history of the diaphragmatic injury on the right in mice

Objective: to evaluate natural evolution of right diaphragmatic injury after the surgical removal of a portion from hemi diaphragm. Methods: the animals were submitted to a surgical removal of portion from right hemi diaphragm by median laparotomy. The sample consists of 42 animals being 2 animals from pilot project and 40 operated animals. And the variables of the study were herniation, liver protection, healing, persistent diaphragm injury, evaluation of 16 channels tomography and the variables "heart rate" and "weight". Results: we analyzed 40 mice, we had two post-operative deaths; we had 17 animals in this group suffered from herniation (42.5%) and 23 animals didn't suffer from herniation (57.5%). Analyzing the tomography as image method in the evaluation of diaphragmatic hernia, we had as a method with good sensitivity (78.6%), good specificity (90.9%), and good accuracy (86.1%) when compared to necropsy. Conclusion: there was a predominance of healing of right hemi diaphragm, the size of initial injury didn't have influence on occurrence of the liver protection or hernia in mice.

University Image vs. University Identity: Congruence between Expectations and Experience

The aim of this thesis was to examine congruencies between university identity and university images of prospective and current students. Therefore, factors essentially influencing on expected and experienced university images were identified. Providing an understanding on the differences in the formation of both concepts allowed the analysis of potential incongruities between a university’s identity and the perceptions its students hold. The study was conducted in July and August 2013 at Lappeenranta University of Technology by means of a web-based research survey. The sample consisted of 160 international Master’s degree students who were admitted in 2011, 2012 and 2013. Descriptive and multivariate statistical analysis methods were used to process the data. The results of the study indicated statistically significant incongruities between the case university’s identity and its students’ images. Further, the expected and experienced university images showed incongruities to each other. Deviations were additionally detected to be dependent on the students’ home regions. All in all, there is potential for an improvement of the students’ experiences resulting from a low perception of the student’s preparation for future job life.

Analysis of trophic responses in lesioned brain: focus on basic fibroblast growth factor mechanisms

The actions of fibroblast growth factors (FGFs), particularly the basic form (bFGF), have been described in a large number of cells and include mitogenicity, angiogenicity and wound repair. The present review discusses the presence of the bFGF protein and messenger RNA as well as the presence of the FGF receptor messenger RNA in the rodent brain by means of semiquantitative radioactive in situ hybridization in combination with immunohistochemistry. Chemical and mechanical injuries to the brain trigger a reduction in neurotransmitter synthesis and neuronal death which are accompanied by astroglial reaction. The altered synthesis of bFGF following brain lesions or stimulation was analyzed. Lesions of the central nervous system trigger bFGF gene expression by neurons and/or activated astrocytes, depending on the type of lesion and time post-manipulation. The changes in bFGF messenger RNA are frequently accompanied by a subsequent increase of bFGF immunoreactivity in astrocytes in the lesioned pathway. The reactive astrocytes and injured neurons synthesize increased amount of bFGF, which may act as a paracrine/autocrine factor, protecting neurons from death and also stimulating neuronal plasticity and tissue repair

Morphometric and ultrastructural analysis of different pituitary cell populations in undernourished monkeys

Undernutrition elicited by a low-protein diet determines a marked reduction of hypophyseal activity and affects the function of the respective target organs. The objective of the present investigation was to study the ultrastructural and quantitative immunohistochemical changes of the different pituitary cell populations in undernourished monkeys that had been previously shown to have significant changes in craniofacial growth. Twenty Saimiri sciureus boliviensis monkeys of both sexes were used. The animals were born in captivity and were separated into two groups at one year of age, i.e., control and undernourished animals. The monkeys were fed ad libitum a 20% (control group) and a 10% (experimental group) protein diet for two years. Pituitaries were processed for light and electron microscopy. The former was immunolabeled with anti-GH, -PRL, -LH, -FSH, -ACTH, and -TSH sera. Volume density and cell density were measured using an image analyzer. Quantitative immunohistochemistry revealed a decrease in these parameters with regard to somatotrophs, lactotrophs, gonadotrophs and thyrotrophs from undernourished animals compared to control ones. In these populations, the ultrastructural study showed changes suggesting compensatory hyperfunction. On the contrary, no significant changes were found in the morphometric parameters or the ultrastructure of the corticotroph population. We conclude that in undernourished monkeys the somatotroph, lactotroph, gonadotroph, and thyrotroph cell populations showed quantitative immunohistochemical changes that can be correlated with ultrastructural findings.

Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

Automatic image-based identification of Saimaa ringed seals

The Saimaa ringed seal is one of the most endangered seals in the world. It is a symbol of Lake Saimaa and a lot of effort have been applied to save it. Traditional methods of seal monitoring include capturing the animals and installing sensors on their bodies. These invasive methods for identifying can be painful and affect the behavior of the animals. Automatic identification of seals using computer vision provides a more humane method for the monitoring. This Master's thesis focuses on automatic image-based identification of the Saimaa ringed seals. This consists of detection and segmentation of a seal in an image, analysis of its ring patterns, and identification of the detected seal based on the features of the ring patterns. The proposed algorithm is evaluated with a dataset of 131 individual seals. Based on the experiments with 363 images, 81\% of the images were successfully segmented automatically. Furthermore, a new approach for interactive identification of Saimaa ringed seals is proposed. The results of this research are a starting point for future research in the topic of seal photo-identification.