Characterisation of pigment particles by scanning electron microscope and image analysis programs

Coating and filler pigments have strong influence to the properties of the paper. Filler content can be even over 30 % and pigment content in coating is about 85-95 weight percent. The physical and chemical properties of the pigments are different and the knowledge of these properties is important for optimising of optical and printing properties of the paper. The size and shape of pigment particles can be measured by different analysers which can be based on sedimentation, laser diffraction, changes in electric field etc. In this master's thesis was researched particle properties especially by scanning electron microscope (SEM) and image analysis programs. Research included nine pigments with different particle size and shape. Pigments were analysed by two image analysis programs (INCA Feature and Poikki), Coulter LS230 (laser diffraction) and SediGraph 5100 (sedimentation). The results were compared to perceive the effect of particle shape to the performance of the analysers. Only image analysis programs gave parameters of the particle shape. One part of research was also the sample preparation for SEM. Individual particles should be separated and distinct in ideal sample. Analysing methods gave different results but results from image analysis programs corresponded even to sedimentation or to laser diffraction depending on the particle shape. Detailed analysis of the particle shape required high magnification in SEM, but measured parameters described very well the shape of the particles. Large particles (ecd~1 µm) could be used also in 3D-modelling which enabled the measurement of the thickness of the particles. Scanning electron microscope and image analysis programs were effective and multifunctional tools for particle analyses. Development and experience will devise the usability of analysing method in routine use.

Making Sense of Women Managers’ Identities through the Constructions of Managerial Career and Gender

This doctoral thesis is about gendered managerial identity construction of women managers. Finnish women managers have been researched from the viewpoints of equality and discrimination issues, careers, and women’s overall positions in work life. However, managerial identity has remained as an unexplored territory. The phenomenon is approached discourse analytically; an interview material that is gathered from 13 women managers in the South-Karelian region is in focus. By studying discourses it is possible to open up understandings how meanings are given to experiences. Women managers’ identity construction is examined from the perspectives of managerial career, managerial practices, and gender. Gender is a meta-concept in this research, as it so profoundly affects our sense of being and acting, although the meaning of it often remains undervalued, invisible, or even denied. This research shows that gender becomes highly visible in managerial contexts, when it is used for some specific purpose, that is, treated as a strategy. By studying women managers it is possible to demystify often so abstract managerial ideals, and open up their taken-for-granted masculine subtexts. It is argued that from the point of view of conducting managerial work, the meaning of self-knowledge appears as critical.

Expertise and decision making among clinicians in investigations of alleged child sexual abuse

The purpose of the present thesis was to explore different aspects of decision making and expertise in investigations of child sexual abuse (CSA) and subsequently shed some light on the reasons for shortcomings in the investigation processes. Clinicians’ subjective attitudes as well as scientifically based knowledge concerning CSA, CSA investigation and interviewing were explored. Furthermore the clinicians’ own view on their expertise and what enhances this expertise was investigated. Also, the effects of scientific knowledge, experience and attitudes on the decision making in a case of CSA were explored. Finally, the effects of different kinds of feedback as well as experience on the ability to evaluate CSA in the light of children’s behavior and base rates were investigated. Both explorative and experimental methods were used. The purpose of Study I was to investigate whether clinicians investigating child sexual abuse (CSA) rely more on scientific knowledge or on clinical experience when evaluating their own expertise. Another goal was to check what kind of beliefs the clinicians held. The connections between these different factors were investigated. A questionnaire covering items concerning demographic data, experience, knowledge about CSA, selfevaluated expertise and beliefs about CSA was given to social workers, child psychiatrists and psychologists working with children. The results showed that the clinicians relied more on their clinical experience than on scientific knowledge when evaluating their expertise as investigators of CSA. Furthermore, social workers possessed stronger attitudes in favor of children than the other groups, while child psychiatrists had more negative attitudes towards the criminal justice system. Male participants held less strong beliefs than female participants. The findings indicate that the education of CSA investigators should focus more on theoretical knowledge and decision making processes as well as the role of beliefs In Study II school and family counseling psychologists completed a Child Sexual Abuse Attitude and Belief Scale. Four CSA related attitude and belief subscales were identified: 1. The Disclosure subscale reflecting favoring a disclosure at any cost, 2. The Pro-Child subscale reflecting unconditional belief in children's reports, 3. The Intuition subscale reflecting favoring an intuitive approach to CSA investigations, and 4. The Anti Criminal Justice System subscale reflecting negative attitudes towards the legal system. Beliefs that were erroneous according to empirical research were analyzed separately. The results suggest that some psychologists hold extreme attitudes and many erroneous beliefs related to CSA. Some misconceptions are common. Female participants tended to hold stronger attitudes than male participants. The more training in interviewing children the participants have, the more erroneous beliefs and stronger attitudes they hold. Experience did not affect attitudes and beliefs. In Study III mental health professionals’ sensitivity to suggestive interviewing in CSA cases was explored. Furthermore, the effects of attitudes and beliefs related to CSA and experience with CSA investigations on the sensitivity to suggestive influences in the interview were investigated. Also, the effect of base rate estimates of CSA on decisions was examined. A questionnaire covering items concerning demographic data, different aspects of clinical experience, self-evaluated expertise, beliefs and knowledge about CSA and a set of ambiguous material based on real trial documents concerning an alleged CSA case was given to child mental health professionals. The experiment was based on a 2 x 2 x 2 x 2 (leading questions: yes vs no) x (stereotype induction: yes vs no) x (emotional tone: pressure to respond vs no pressure to respond) x (threats and rewards: yes vs no) between-subjects factorial design, in which the suggestiveness of the methods with which the responses of the child were obtained were varied. There was an additional condition in which the material did not contain any interview transcripts. The results showed that clinicians are sensitive only to the presence of leading questions but not to the presence of other suggestive techniques. Furthermore, the clinicians were not sensitive to the possibility that suggestive techniques could have been used when no interview transcripts had been included in the trial material. Experience had an effect on the sensitivity of the clinicians only regarding leading questions. Strong beliefs related to CSA lessened the sensitivity to leading questions. Those showing strong beliefs on the belief scales used in this study were even more prone to prosecute than other participants when other suggestive influences than leading questions were present. Controversy exists regarding effects of experience and feedback on clinical decision making. In Study IV the impact of the number of handled cases and of feedback on the decisions in cases of alleged CSA was investigated. One-hundred vignettes describing cases of suspected CSA were given to students with no experience with investigating CSA. The vignettes were based on statistical data about symptoms and prevalence of CSA. According to the theoretical likelihood of CSA the children described were categorized as abused or not abused. The participants were asked to decide whether abuse had occurred. They were divided into 4 groups: one received feedback on whether their decision was right or wrong, one received information about cognitive processes involved in decision making, one received both, and one did not receive feedback at all. The results showed that participants who received feedback on their performance made more correct positive decisions and participants who got information about decision making processes made more correct negative decisions. Feedback and information combined decreased the number of correct positive decisions but increased the number of correct negative decisions. The number of read cases had in itself a positive effect on correct positive decision.

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

Computational Techniques for Spectral Image Analysis

Multispectral images are becoming more common in the field of remote sensing, computer vision, and industrial applications. Due to the high accuracy of the multispectral information, it can be used as an important quality factor in the inspection of industrial products. Recently, the development on multispectral imaging systems and the computational analysis on the multispectral images have been the focus of a growing interest. In this thesis, three areas of multispectral image analysis are considered. First, a method for analyzing multispectral textured images was developed. The method is based on a spectral cooccurrence matrix, which contains information of the joint distribution of spectral classes in a spectral domain. Next, a procedure for estimating the illumination spectrum of the color images was developed. Proposed method can be used, for example, in color constancy, color correction, and in the content based search from color image databases. Finally, color filters for the optical pattern recognition were designed, and a prototype of a spectral vision system was constructed. The spectral vision system can be used to acquire a low dimensional component image set for the two dimensional spectral image reconstruction. The data obtained by the spectral vision system is small and therefore convenient for storing and transmitting a spectral image.

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.