Using adaptive thresholding and skewness correction to detect gray areas in melanoma \u3ci\u3ein situ\u3c/i\u3e images

The incidence of melanoma in situ (MIS) is growing significantly. Detection at the MIS stage provides the highest cure rate for melanoma, but reliable detection of MIS with dermoscopy alone is not yet possible. Adjunct dermoscopic instrumentation using digital image analysis may allow more accurate detection of MIS. Gray areas are a critical component of MIS diagnosis, but automatic detection of these areas remains difficult because similar gray areas are also found in benign lesions. This paper proposes a novel adaptive thresholding technique for automatically detecting gray areas specific to MIS. The proposed model uses only MIS dermoscopic images to precisely determine gray area characteristics specific to MIS. To this aim, statistical histogram analysis is employed in multiple color spaces. It is demonstrated that skew deviation due to an asymmetric histogram distorts the color detection process. We introduce a skew estimation technique that enables histogram asymmetry correction facilitating improved adaptive thresholding results. These histogram statistical methods may be extended to detect any local image area defined by histograms --Abstract, page iv

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

Phenotypic and Genotypic Studies in the Peach [Prunus persica (L.) Batsch] and Muscadine Grape (Vitis rotundifolia Michx.)

Peach: Peaches [Prunus persica (L.) Batsch] are routinely chilled to increase shelf-life. Exposure to temperatures of 5° C for two weeks can induce chilling injury (CI) symptoms, including flesh mealiness (or wooliness) and a lack of juiciness. Phenotypic data were collected on seven biparental F1 peach populations maintained at the University of Arkansas Fruit Research Station. A genome wide association study (GWAS) was performed using TASSEL 5 which identified four quantitative trait loci (QTLs) associated with expressible juice, four QTLs for mealiness, five QTLs for soluble solids, and three QTLs for fruit weight. Exploiting these genetic markers could help breeders identify fruit quality traits in seedlings through marker-assisted selection (MAS). Muscadine: Two biparental F1 muscadine (Vitis rotundifolia Michx.) populations were phenotyped for flower sex and berry color, and genotyping-by-sequencing (GBS) was performed to produce high-density genetic linkage maps. A total of 1244 SNP markers in population Black Beauty [BB] x Nesbitt [N] and 2069 SNP markers in population Supreme [S] x Nesbitt [N] were mapped to 20 linkage groups (LG) for each population. The results support previous studies revealing an evolutionary bifurcation of V. vinifera chromosome 7 into two independently segregating linkage groups in the muscadine, or, conversely, a possible fusion of muscadine-derived chromosomes into chromosome 7 of V. vinifera. The locus controlling flower type in muscadine mapped to a region spanning 4.6 – 5.1 Mbp on chromosome 2, while the berry color locus mapped to a region spanning 11.1-11.9 Mbp on chromosome 4. These high-density linkage maps lay the groundwork for marker-assisted selection (MAS) in muscadine and provide clues to the evolutionary relationship of the muscadine with V. vinifera. Colorimetry: Precise color identification is critical in many scientific fields, and horticulture is no exception. Plant breeders must be able to effectively discern colors among plant parts and provide accurate descriptions when applying for legal protections. The RHS Colour Chart is currently recognized as the most universally accepted method of assigning color descriptions in horticulture. The RHS Colour Chart relies on manually matching plant parts with the labeled color chips provided. Color perception in humans is complicated by many factors, including the type and quantity of illumination available as well as the individual’s own physiological abilities and limitations. Scientific colorimeters have been developed to serve as an objective way to study color, and many hypothetical color space models have been created to enhance this field of study. The CIE 1976 L*a*b* (CIELAB) color space is widely recognized as a scientific standard and was used in this study. Traditional colorimeters have been bulky and expensive lab equipment, but a new, portable, inexpensive LED-based color scanner called the Nix Pro Color Sensor™ has recently become available. Multiple studies were conducted comparing the Nix Pro with the Konica Minolta CR-400 colorimeter and the RHS Colour Chart paint chip system. The results indicate the Nix Pro, which is inexpensive, yields consistent results, and features built-in color matching capabilities, could be a very useful tool for horticulturists and plant breeders

Computer mediated colour fidelity and communication

Developments in technology have meant that computercontrolled imaging devices are becoming more powerful and more affordable. Despite their increasing prevalence, computer-aided design and desktop publishing software has failed to keep pace, leading to disappointing colour reproduction across different devices. Although there has been a recent drive to incorporate colour management functionality into modern computer systems, in general this is limited in scope and fails to properly consider the way in which colours are perceived. Furthermore, differences in viewing conditions or representation severely impede the communication of colour between groups of users. The approach proposed here is to provide WYSIWYG colour across a range of imaging devices through a combination of existing device characterisation and colour appearance modeling techniques. In addition, to further facilitate colour communication, various common colour notation systems are defined by a series of mathematical mappings. This enables both the implementation of computer-based colour atlases (which have a number of practical advantages over physical specifiers) and also the interrelation of colour represented in hitherto incompatible notations. Together with the proposed solution, details are given of a computer system which has been implemented. The system was used by textile designers for a real task. Prior to undertaking this work, designers were interviewed in order to ascertain where colour played an important role in their work and where it was found to be a problem. A summary of the findings of these interviews together with a survey of existing approaches to the problems of colour fidelity and communication in colour computer systems are also given. As background to this work, the topics of colour science and colour imaging are introduced

Text Segmentation in Web Images Using Colour Perception and Topological Features

The research presented in this thesis addresses the problem of Text Segmentation in Web images. Text is routinely created in image form (headers, banners etc.) on Web pages, as an attempt to overcome the stylistic limitations of HTML. This text however, has a potentially high semantic value in terms of indexing and searching for the corresponding Web pages. As current search engine technology does not allow for text extraction and recognition in images, the text in image form is ignored. Moreover, it is desirable to obtain a uniform representation of all visible text of a Web page (for applications such as voice browsing or automated content analysis). This thesis presents two methods for text segmentation in Web images using colour perception and topological features. The nature of Web images and the implicit problems to text segmentation are described, and a study is performed to assess the magnitude of the problem and establish the need for automated text segmentation methods. Two segmentation methods are subsequently presented: the Split-and-Merge segmentation method and the Fuzzy segmentation method. Although approached in a distinctly different way in each method, the safe assumption that a human being should be able to read the text in any given Web Image is the foundation of both methods’ reasoning. This anthropocentric character of the methods along with the use of topological features of connected components, comprise the underlying working principles of the methods. An approach for classifying the connected components resulting from the segmentation methods as either characters or parts of the background is also presented