Titlebook: Content-Based Image Retrieval; Ideas, Influences, a Vipin Tyagi Book 2017 Springer Nature Singapore Pte Ltd. 2017 Image Retreival.Image Sea

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Content-Based Image Retrieval Using Integrated Color, Texture, and Shape Features,each block. All three features are combined to make a single completed binary region descriptor (CBRD) represented in the LBP way. To support region-based retrieval, an effective region code-based scheme is employed. In this technique, the spatial relative locations of objects are also considered to increase the retrieval accuracy.

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Region-Based Image Retrieval,f interests are capable of reflecting user-specific interest with greater accuracy. However, success of automatic selection of region of interest-based methods largely depends on the segmentation technique used. In this chapter, state-of-the-art techniques for region-based image retrieval are discussed.

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Similarity Measures and Performance Evaluation,of the system in terms of output generated in response to a query, in comparison to other state-of-the-art systems. This chapter also describes some common measures that are used to evaluate the performance on CBIR systems.

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