Combinatorial Image Analysis [electronic resource] : 17th International Workshop, IWCIA 2015, Kolkata, India, November 24-27, 2015. Proceedings / edited by Reneta P. Barneva, Bhargab B. Bhattacharya, Valentin E. Brimkov.

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Series: Lecture Notes in Computer Science ; 9448Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015Description: XIII, 363 p. 177 illus. in color. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783319261454

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Electronic books.

Additional physical formats: Printed edition:: No titleDDC classification:

006.6 23
006.37 23

LOC classification:

TA1637-1638
TA1634

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In: Springer eBooksSummary: This volume constitutes the refereed proceedings of the 17th International Workshop on Combinatorial Image Analysis, IWCIA 2015, held in Kolkata, India, in November 2015. The 24 revised full papers and 2 invited papers presented were carefully reviewed and selected from numerous submissions. The workshop provides theoretical foundations and methods for solving problems from various areas of human practice. In contrast to traditional approaches to image analysis which implement continuous models, float arithmetic and rounding, combinatorial image analysis features discrete modelsusing integer arithmetic. The developed algorithms are based on studying combinatorial properties of classes of digital images, and often appear to be more efficient and accurate than those based on continuous models.

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eBooks

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This volume constitutes the refereed proceedings of the 17th International Workshop on Combinatorial Image Analysis, IWCIA 2015, held in Kolkata, India, in November 2015. The 24 revised full papers and 2 invited papers presented were carefully reviewed and selected from numerous submissions. The workshop provides theoretical foundations and methods for solving problems from various areas of human practice. In contrast to traditional approaches to image analysis which implement continuous models, float arithmetic and rounding, combinatorial image analysis features discrete modelsusing integer arithmetic. The developed algorithms are based on studying combinatorial properties of classes of digital images, and often appear to be more efficient and accurate than those based on continuous models.