Color models and their properties; Color feature extraction: color histogram, color coherence vector, color correlogram, dominant color descriptor, scalable color descriptor, color structure descriptor, color naming system; Texture feature extraction: moment based texture features, gray level co-occurrence matrix, features based on Gabor filter, wavelet and curvelet transforms, simultaneous autoregressive model, fractal dimension, edge detection and edge histogram; Shape feature extraction: image segmentation, contour representation by chain codes, Fourier descriptors, and curvature scale space, region descriptors; local and global features; Distance measures; Performance metrics; Databases; Tradition metadata based image retrieval; Content based image retrieval (CBIR) using low level color, texture and shape features; Issues in CBIR; Relevance feedback in image retrieval; Image understanding using support vector machines, neural networks, decision tree, Bayesian theorem, and ontology; Semantic image retrieval; Web image retrieval.
- Teacher: Test Asteacher