This comprehensive textbook covers the fundamentals of data retrieval and image retrieval using extrema patterns, making it an ideal resource for senior undergraduate and graduate students in electrical engineering and electronics and communications engineering. It details various types of texture-dependent image patterns for retrieval, including Improved Directional Local Extrema Patterns, Local Quantized Extrema Patterns, Local Color Oppugnant Quantized Extrema Patterns, and Local Mesh Quantized Extrema Patterns. The book emphasizes the inter-relationships among pixels for feature extraction, focusing on the local neighborhood to create feature vectors. Evaluation metrics such as precision and recall are calculated using standard databases like Corel-1k, Corel-5k, and MIT VisTex. Additionally, it introduces two models of Directional Local Extrema Patterns: the integration of color and directional patterns, and the integration of Gabor features. It provides a framework for feature extraction using quantization methods and discusses local quantized extrema from two oppugnant color planes, illustrated through a mesh structure with pixels in alternate positions. The content is organized into chapters covering introduction, features for image retrieval, various local patterns, applications, and future scope.
