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 a Short Run Length Descriptor,image local and global information. It can be viewed as an integrated representation of both color and texture properties. HSV color space is quantized to 72 bins, and SRLD is computed using short run lengths of size 2 and 3 for each color in different orientations. Short run lengths at all orientat

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Multistage Content-Based Image Retrieval,produced for these features are merged using data fusion techniques to produce one common output. In this chapter, an image retrieval technique is described, which retrieves similar color images in three stages. Initially, a fixed number of images are retrieved based on their color feature similarit

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Alaa A. A. Aljabali,David J. Evansval and content-based image retrieval techniques are introduced. A brief introduction to visual features like color, texture, and shape is provided. Similarity measures used in content-based image retrieval and performance evaluation of content-based image retrieval techniques are also given. Import

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Case Study: An Event-Driven Language,superior to the single-dimensional gray values of images. Color can be retrieved easily from images without any complex preprocessing. Color feature is robust to background complication and invariant of image size and orientation of the image. There are many color spaces designed for different syste

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https://doi.org/10.1007/978-1-84628-246-1ncept of texture is introduced and a number of texture features are described. Various models of the texture are discussed which can be used in content-based image retrieval. A brief description of MPEG-7 texture descriptors is also provided.