Margarida Ruela, Catarina Barata, Jorge S. Marques (auth.),'s Advances in Visual Computing: 9th International Symposium, PDF

By Margarida Ruela, Catarina Barata, Jorge S. Marques (auth.), George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Baoxin Li, Fatih Porikli, Victor Zordan, James Klosowski, Sabine Coquillart, Xun Luo, Min Chen, David Gotz (eds.)

ISBN-10: 3642419135

ISBN-13: 9783642419133

ISBN-10: 3642419143

ISBN-13: 9783642419140

The quantity units LNCS 8033 and 8034 constitutes the refereed court cases of the ninth overseas Symposium on visible Computing, ISVC 2013, held in Rethymnon, Crete, Greece, in July 2013. The sixty three revised complete papers and 35 poster papers offered including 32 detailed song papers have been conscientiously reviewed and chosen from greater than 220 submissions. The papers are prepared in topical sections: half I (LNCS 8033) includes computational bioimaging; special effects; movement, monitoring and popularity; segmentation; visualization; 3D mapping, modeling and floor reconstruction; function extraction, matching and popularity; sparse tools for computing device imaginative and prescient, pix and scientific imaging; and face processing and popularity. half II (LNCS 8034) includes subject matters reminiscent of visualization; visible computing with multimodal information streams; visible computing in electronic cultural historical past; clever environments: algorithms and purposes; functions and digital reality.

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Read Online or Download Advances in Visual Computing: 9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part I PDF

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Extra resources for Advances in Visual Computing: 9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part I

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20(3), 233–239 (2001) 8. : Can early malignant melanoma be differenciated from atypical melanocytic nevus by in vivo techniques? Part II. Automatic machine vision classification. Skin Research and Technology 3, 15–22 (1997) 9. : Towards a computer-aided diagnosis system for pigmented skin lesions. Computerized Medical Imaging and Graphics 27(1), 65–78 (2003) 10. : Pigment distribution in melanocytic lesion images: a digital parameter to be employed for computer-aided diagnosis. Skin Research and Technology 11, 236–241 (2005) 11.

The pseudo code is as follows: if I ( x, y ) − I ( x − 1, y ) ≥ I ( x, y ) − I ( x + 1, y ) HG ( x, y ) = I ( x, y ) − I ( x − 1, y ) else HG ( x, y ) = I ( x, y ) − I ( x + 1, y ) where I ( x, y ) is the intensity of current pixel pixel ( x, y ) , I ( x − 1, y ) is the intensity of its left pixel pixel ( x − 1, y ) and I ( x + 1, y ) is the intensity of its right pixel pixel ( x + 1, y ) . A pixel is selected as a border pixel if it satisfies two conditions: 1). Its horizontal gradient value is larger than thirty: HG ( x, y ) ≥ 30 .

Most of them rely on the extraction of several types of visual features: color, texture and shape. However, the role of each type of feature is seldom assessed. This paper proposes several features for the analysis of color symmetry in skin lesions and assesses their performance under a wide variety of system configurations. We have obtained very high detection scores (SE=96%, SP=83%) by only using color symmetry features, showing that they play a major role in the analysis of dermoscopy images.

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Advances in Visual Computing: 9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings, Part I by Margarida Ruela, Catarina Barata, Jorge S. Marques (auth.), George Bebis, Richard Boyle, Bahram Parvin, Darko Koracin, Baoxin Li, Fatih Porikli, Victor Zordan, James Klosowski, Sabine Coquillart, Xun Luo, Min Chen, David Gotz (eds.)


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