Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifying malignant melanoma. Dermoscopy Image Analysis summarizes the state of the art of the computerized analysis of dermoscopy images. The book begins by discussing the influence of color normalization on classification accuracy and then: Investigates gray-world, max-RGB, and shades-of-gray color constancy algorithms, showing significant gains in sensitivity and specificity on a heterogeneous set of images Proposes a new color space that highlights the distribution of underlying melanin and hemoglobin color pigments, leading to more accurate classification and border detection results Determines that the latest border detection algorithms can achieve a level of agreement that is only slightly lower than the level of agreement among experienced dermatologists Provides a comprehensive review of various methods for border detection, pigment network extraction, global pattern extraction, streak detection, and perceptually significant color detection Details a computer-aided diagnosis (CAD) system for melanomas that features an inexpensive acquisition tool, clinically meaningful features, and interpretable classification feedback Presents a highly scalable CAD system implemented in the MapReduce framework, a novel CAD system for melanomas, and an overview of dermatological image databases Describes projects that made use of a publicly available database of dermoscopy images, which contains 200 high-quality images along with their medical annotations Dermoscopy Image Analysis not only showcases recent advances but also explores future directions for this exciting subfield of medical image analysis, covering dermoscopy image analysis from preprocessing to classification.

IbPRIA 2005 (Iberian Conference on Pattern Recognition and Image Analysis) was the second of a series of conferences jointly organized every two years by the Portuguese and Spanish Associations for Pattern Recognition (APRP, AERFAI), with the support of the International Association for Pattern Recognition (IAPR). This year, IbPRIA was hosted by the Institute for Systems and Robotics and the Geo-systems Center of the Instituto Superior Tecn ico and it was held in Estoril, Por- gal. It provided the opportunity to bring together researchers from all over the world to discuss some of the most recent advances in pattern recognition and all areas of video, image and signal processing. There was a very positive response to the Call for Papers for IbPRIA 2005. We - ceived 292 full papers from 38 countries and 170 were accepted for presentation at the conference. The high quality of the scienti?c program of IbPRIA 2005 was due ?rst to the authors who submitted excellent contributions and second to the dedicated colla- ration of the international Program Committee and the other researchers who reviewed the papers. Each paper was reviewed by two reviewers, in a blind process. We would like to thank all the authors for submitting their contributions and for sharing their - search activities. We are particularly indebted to the Program Committee members and to all the reviewers for their precious evaluations, which permitted us to set up this publication."

IbPRIA 2005 (Iberian Conference on Pattern Recognition and Image Analysis) was the second of a series of conferences jointly organized every two years by the Portuguese and Spanish Associations for Pattern Recognition (APRP, AERFAI), with the support of the International Association for Pattern Recognition (IAPR). This year, IbPRIA was hosted by the Institute for Systems and Robotics and the Geo-systems Center of the Instituto Superior Tecn ico and it was held in Estoril, Por- gal. It provided the opportunity to bring together researchers from all over the world to discuss some of the most recent advances in pattern recognition and all areas of video, image and signal processing. There was a very positive response to the Call for Papers for IbPRIA 2005. We - ceived 292 full papers from 38 countries and 170 were accepted for presentation at the conference. The high quality of the scienti?c program of IbPRIA 2005 was due ?rst to the authors who submitted excellent contributions and second to the dedicated colla- ration of the international Program Committee and the other researchers who reviewed the papers. Each paper was reviewed by two reviewers, in a blind process. We would like to thank all the authors for submitting their contributions and for sharing their - search activities. We are particularly indebted to the Program Committee members and to all the reviewers for their precious evaluations, which permitted us to set up this publication."

Dermoscopy is a noninvasive skin imaging technique that uses optical magnification and either liquid immersion or cross-polarized lighting to make subsurface structures more easily visible when compared to conventional clinical images. It allows for the identification of dozens of morphological features that are particularly important in identifying malignant melanoma. Dermoscopy Image Analysis summarizes the state of the art of the computerized analysis of dermoscopy images. The book begins by discussing the influence of color normalization on classification accuracy and then: Investigates gray-world, max-RGB, and shades-of-gray color constancy algorithms, showing significant gains in sensitivity and specificity on a heterogeneous set of images Proposes a new color space that highlights the distribution of underlying melanin and hemoglobin color pigments, leading to more accurate classification and border detection results Determines that the latest border detection algorithms can achieve a level of agreement that is only slightly lower than the level of agreement among experienced dermatologists Provides a comprehensive review of various methods for border detection, pigment network extraction, global pattern extraction, streak detection, and perceptually significant color detection Details a computer-aided diagnosis (CAD) system for melanomas that features an inexpensive acquisition tool, clinically meaningful features, and interpretable classification feedback Presents a highly scalable CAD system implemented in the MapReduce framework, a novel CAD system for melanomas, and an overview of dermatological image databases Describes projects that made use of a publicly available database of dermoscopy images, which contains 200 high-quality images along with their medical annotations Dermoscopy Image Analysis not only showcases recent advances but also explores future directions for this exciting subfield of medical image analysis, covering dermoscopy image analysis from preprocessing to classification.