000 03956nam a22005535i 4500
001 978-3-319-26462-2
003 DE-He213
005 20200420221248.0
007 cr nn 008mamaa
008 151107s2016 gw | s |||| 0|eng d
020 _a9783319264622
_9978-3-319-26462-2
024 7 _a10.1007/978-3-319-26462-2
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aCuevas, Erik.
_eauthor.
245 1 0 _aApplications of Evolutionary Computation in Image Processing and Pattern Recognition
_h[electronic resource] /
_cby Erik Cuevas, Daniel Zald�ivar, Marco Perez-Cisneros.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXV, 274 p. 111 illus., 55 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v100
505 0 _aIntroduction -- Image Segmentation Based on Differential Evolution Optimization.-Motion Estimation Based on Artificial Bee Colony (ABC) -- Ellipse Detection on Images Inspired by the Collective Animal Behavior -- Template Matching by Using the States of Matter Algorithm -- Estimation of Multiple View Relations Considering Evolutionary Approaches -- Circle Detection on Images Based on an Evolutionary Algorithm that Reduces the Number of Function Evaluations -- Otsu and Kapur Segmentation Based on Harmony Search Optimization -- Leukocyte Detection by Using Electromagnetism-Like Optimization -- Automatic Segmentation by Using an Algorithm Based on the Behavior of Locust Swarms.
520 _aThis book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the different aspects of evolutionary methods in order to enable the reader in reaching a global understanding of the field and, in conducting studies on specific evolutionary techniques that are related to applications in image processing and pattern recognition. It explains the basic ideas of the proposed applications in a way that can also be understood by readers outside of the field. Image processing and pattern recognition practitioners who are not evolutionary computation researchers will appreciate the discussed techniques beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise on such areas. On the other hand, members of the evolutionary computation community can learn the way in which image processing and pattern recognition problems can be translated into an optimization task. The book has been structured so that each chapter can be read independently from the others. It can serve as reference book for students and researchers with basic knowledge in image processing and EC methods.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 0 _aImage processing.
650 0 _aCalculus of variations.
650 0 _aComputational intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aSignal, Image and Speech Processing.
650 2 4 _aImage Processing and Computer Vision.
650 2 4 _aCalculus of Variations and Optimal Control; Optimization.
700 1 _aZald�ivar, Daniel.
_eauthor.
700 1 _aPerez-Cisneros, Marco.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319264608
830 0 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v100
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-26462-2
912 _aZDB-2-ENG
942 _cEBK
999 _c52432
_d52432