000			03247 a2200217 4500
003			OSt
020			_a9781032234588, 9781032660325
040			_cIIT Kanpur
041			_aeng
082			_a006.6 _bC894i
100			_aCuevas, Erik
245			_aImage processing and machine learning [2 Vols.] _cErik Cuevas and Alma Nayeli Rodríguez
260			_bCRC Press _c2024 _aBoca Raton
300			_aVarious pagings
505			_av.1. Foundations of image processing, pg. xiii, 209p., 9781032234588: A186670; v.2.Advanced topics in image analysis and machine learning, pg. xiv, 223p., 9781032660325: A186671
520			_aVol.1. Image processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches. Divided into two volumes, this first installment explores the fundamental concepts and techniques in image processing, starting with pixel operations and their properties and exploring spatial filtering, edge detection, image segmentation, corner detection, and geometric transformations. It provides a solid foundation for readers interested in understanding the core principles and practical applications of image processing, establishing the essential groundwork necessary for further explorations covered in Volume 2. Written with instructors and students of image processing in mind, this book’s intuitive organization also contains appeal for app developers and engineers. Vol.2. Image processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches. Divided into two volumes, this second installment explores the more advanced concepts and techniques in image processing, including morphological filters, color image processing, image matching, feature-based segmentation utilizing the mean shift algorithm, and the application of singular value decomposition for image compression. This second volume also incorporates several important machine learning techniques applied to image processing, building on the foundational knowledge introduced in Volume 1. Written with instructors and students of image processing in mind, this book’s intuitive organization also contains appeal for app developers and engineers.
650			_aImage processing
650			_aMachine learning
700			_aRodríguez, Alma Nayeli
942			_cBK
999			_c567376 _d567376