LEADER 00853nam a2200253 i 4500 001 991003429739707536 005 20021217150958.0 008 970611s1983 it a 000 0 ita d 035 $ab11807313-39ule_inst 035 $aLE00300331$9ExL 040 $aDip.to Biologia$beng 082 0 $a572$222 100 1 $aLusini, Paola$0531165 245 10$aBiochimica dell'occhio /$cPaola Lusini 260 $aPadova :$bPiccin,$cc1983 300 $a88 p. :$bill. ;$c24 cm 490 0 $aQuaderni di biochimica ;$v30 650 4$aEyes 907 $a.b11807313$b27-04-17$c18-12-02 912 $a991003429739707536 945 $aLE003 572 QUA01.01 V.30 (1983)$g1$i2003000006117$lle003$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i12055943$z18-12-02 996 $aBiochimica dell'occhio$9907587 997 $aUNISALENTO 998 $ale003$b01-01-97$cm$da $e-$fita$git $h0$i1 LEADER 03600nam 2200493 450 001 9910155078903321 005 20211109143727.0 010 $a1-4919-3800-5 010 $a1-4919-3798-X 010 $a1-4919-3796-3 035 $a(CKB)3710000000973354 035 $a(MiAaPQ)EBC4770094 035 $a(PPN)22010350X 035 $a(CaSebORM)9781491937983 035 $a(EXLCZ)993710000000973354 100 $a20170103h20172017 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLearning OpenCV 3 $ecomputer Vision in C++ with the OpenCV Library /$fAdrian Kaehler and Gary Bradski 205 $aFirst edition. 210 1$aBeijing, [China] :$cO'Reilly Media,$d2017. 210 4$dİ2017 215 $a1 online resource (1,018 pages) $cillustrations 300 $aDescription based upon print version of record. 311 $a1-4919-3799-8 320 $aIncludes bibliographical references and index. 327 $a1. Overview -- 2. Introduction to OpenCV -- 3. Getting to know OpenCV data types -- 4. Images and Large Array Types -- 5. Array Operations -- 6. Drawing and Annotating -- 7. Functors in OpenCV -- 8. Image, Video, and Data Files -- 9. Cross-Platform and Native Windows -- 10. Filters and Convolution -- 11. General Image Transforms -- 12. Image Analysis -- 13. Histograms and Templates -- 14. Contours -- 15. Background Subtraction -- 16. Keypoints and Descriptors -- 17. Tracking -- 18. Camera Models and Calibration -- 19. Projection and Three-Dimensional Vision -- 20. The Basics of Machine Learning in OpenCV -- 21. StatModel: The Standard Model for Learning in OpenCV -- 22. Object Detection -- 23. Future of OpenCV -- A. Planar Subdivisions -- B. opencv_contrib -- C. Calibration Patterns. 330 $aGet started in the rapidly expanding field of computer vision with this practical guide. Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, roboticists, and hobbyists. You'll learn what it takes to build applications that enable computers to "see" and make decisions based on that data. With over 500 functions that span many areas in vision, OpenCV is used for commercial applications such as security, medical imaging, pattern and face recognition, robotics, and factory product inspection. This book gives you a firm grounding in computer vision and OpenCV for building simple or sophisticated vision applications. Hands-on exercises in each chapter help you apply what you've learned. This volume covers the entire library, in its modern C++ implementation, including machine learning tools for computer vision. Learn OpenCV data types, array types, and array operations. Capture and store still and video images with HighGUI. Transform images to stretch, shrink, warp, remap, and repair Explore pattern recognition, including face detection. Track objects and motion through the visual field Reconstruct 3D images from stereo vision. Discover basic and advanced machine learning techniques in OpenCV. 517 3 $aComputer vision in C++ with the OpenCV library 606 $aImage processing$xDigital techniques 615 0$aImage processing$xDigital techniques. 676 $a621.367 700 $aKaehler$b Adrian$0504508 702 $aBradski$b Gary 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910155078903321 996 $aLearning OpenCV 3$91905501 997 $aUNINA