Fuzzy Image Processing and Applications with MATLAB

摘要: In contrast to classical image analysis methods that employ "crisp" mathematics, fuzzy set techniques provide an elegant foundation and a of rich methodologies for diverse image-processing tasks. However, solid understanding processing requires firm grasp essential principles background knowledge. Fuzzy Image Processing Applications with MATLAB presents the integral science mathematics behind this exciting dynamic branch processing, which is becoming increasingly important applications in areas such as remote sensing, medical imaging, video surveillance, name few. Many texts cover use crisp sets, but book stands apart by exploring explosion interest significant growth processing. The distinguished authors clearly lay out theoretical concepts theory their impact on enhancement, segmentation, filtering, edge detection, content-based retrieval, pattern recognition, clustering. They describe all components fuzzy, detailing preprocessing, threshold match-based segmentation. Minimize Errors Using Dynamic Set Theory This serves primer demonstrates how implement it methods. It illustrates code can be used improve calculations help prevent or deal imprecisionwhether grey level image, geometry object, definition objects edges boundaries, knowledge representation, object interpretation. text addresses these considerations applying thresholding, clustering, color clustering other operations. Highlighting key ideas, present experimental results own new approaches those suggested different authors, offering data insights will useful teachers, scientists, engineers, among others.