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M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 5 Issue 6, June 2016

An Adaptive Histogram Values & Texture Descriptor for Data Analysis

Ritika Verma | Vinay Thakur

Abstract: Image Retrieval Systems is a useful method for pattern recognition and artificial intelligence. There are three methods used for image retrieval such as Content based image retrieval, Text based image retrieval system and Semantic based image retrieval. In content based image retrieval system, images are stored by visual content, such as Texture, Shape, Layout and Color. Color, Texture, Shape and Layout are the primitive methods which are used in content based image retrieval system. In this paper presents a methodology which compares the images with the database using different types of parameters and gives the resulted image which is closely matched with the query image. For being this purpose using a five parameters for analysis image such as Entropy, Correlation, Standard Deviation, Contrast and Local Range. Histogram Values are used to extract the color properties of an image. The Combine feature of color and texture of images providing a robust feature for image retrieval. It achieves a experimental results which give the elapsed time for searching the image.

Keywords: CBIR, Texture Extraction, Color Histogram, Image Texture, Pattern Recognition

Edition: Volume 5 Issue 6, June 2016,

Pages: 2318 - 2322