Combinatorial Image Analysis 17th International Workshop, IWCIA 2015, Kolkata, India, November 24-27, 2015. Proceedings / [electronic resource] :
edited by Reneta P. Barneva, Bhargab B. Bhattacharya, Valentin E. Brimkov.
- 1st ed. 2015.
- XIII, 363 p. 177 illus. in color. online resource.
- Lecture Notes in Computer Science, 9448 0302-9743 ; .
- Lecture Notes in Computer Science, 9448 .
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.
9783319261454
10.1007/978-3-319-26145-4 doi
Computer science.
Algorithms.
Computer science--Mathematics.
Artificial intelligence.
Computer graphics.
Image processing.
Pattern recognition.
Computer Science.
Image Processing and Computer Vision.
Computer Graphics.
Pattern Recognition.
Artificial Intelligence (incl. Robotics).
Algorithm Analysis and Problem Complexity.
Discrete Mathematics in Computer Science.
TA1637-1638 TA1634
006.6 006.37
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.
9783319261454
10.1007/978-3-319-26145-4 doi
Computer science.
Algorithms.
Computer science--Mathematics.
Artificial intelligence.
Computer graphics.
Image processing.
Pattern recognition.
Computer Science.
Image Processing and Computer Vision.
Computer Graphics.
Pattern Recognition.
Artificial Intelligence (incl. Robotics).
Algorithm Analysis and Problem Complexity.
Discrete Mathematics in Computer Science.
TA1637-1638 TA1634
006.6 006.37