LEADER 03862nam 22007695 450 001 9910254194503321 005 20200706082243.0 010 $a3-662-47794-7 024 7 $a10.1007/978-3-662-47794-6 035 $a(CKB)3710000000484452 035 $a(EBL)4178911 035 $a(SSID)ssj0001584671 035 $a(PQKBManifestationID)16264457 035 $a(PQKBTitleCode)TC0001584671 035 $a(PQKBWorkID)14866408 035 $a(PQKB)10620639 035 $a(DE-He213)978-3-662-47794-6 035 $a(MiAaPQ)EBC4178911 035 $a(PPN)190518650 035 $a(EXLCZ)993710000000484452 100 $a20150826d2016 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aMachine Vision $eAutomated Visual Inspection: Theory, Practice and Applications /$fby Jürgen Beyerer, Fernando Puente León, Christian Frese 205 $a1st ed. 2016. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2016. 215 $a1 online resource (802 p.) 300 $aDescription based upon print version of record. 311 $a3-662-47793-9 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aIntroduction -- Part I Image Acquisition: Light -- Optical Imaging -- Radiometry -- Color -- Sensors for Image Acquisition -- Methods for Image Acquisition -- Part II Image Processing: Image Signals -- Preprocessing and Image Enhancement -- Image Restoration -- Segmentation -- Morphological Image Processing -- Texture Analysis -- Detection -- Image Pyramids, Wavelet Transform and Multiresolution Analysis -- Mathematical Foundations -- The Fourier Transform. 330 $aThe book offers a thorough introduction to machine vision. It is organized in two parts. The first part covers the image acquisition, which is the crucial component of most automated visual inspection systems. All important methods are described in great detail and are presented with a reasoned structure. The second part deals with the modeling and processing of image signals and pays particular regard to methods, which are relevant for automated visual inspection. 606 $aSignal processing 606 $aImage processing 606 $aSpeech processing systems 606 $aOptical data processing 606 $aRobotics 606 $aAutomation 606 $aPhysical measurements 606 $aMeasurement    606 $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051 606 $aImage Processing and Computer Vision$3https://scigraph.springernature.com/ontologies/product-market-codes/I22021 606 $aRobotics and Automation$3https://scigraph.springernature.com/ontologies/product-market-codes/T19020 606 $aMeasurement Science and Instrumentation$3https://scigraph.springernature.com/ontologies/product-market-codes/P31040 615 0$aSignal processing. 615 0$aImage processing. 615 0$aSpeech processing systems. 615 0$aOptical data processing. 615 0$aRobotics. 615 0$aAutomation. 615 0$aPhysical measurements. 615 0$aMeasurement   . 615 14$aSignal, Image and Speech Processing. 615 24$aImage Processing and Computer Vision. 615 24$aRobotics and Automation. 615 24$aMeasurement Science and Instrumentation. 676 $a620 700 $aBeyerer$b Jürgen$4aut$4http://id.loc.gov/vocabulary/relators/aut$01029954 702 $aPuente León$b Fernando$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aFrese$b Christian$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910254194503321 996 $aMachine Vision$92544030 997 $aUNINA