Content-Based Image Retrieval using HSV and Hadamard DWT

Abstract

With the development of the Internet, and the availability of image capturing devices such as digital cameras, image scanners, the size of digital image collection is increasing rapidly. For this purpose, many general purpose image retrieval systems have been developed. In CBIR, images are indexed by their visual content. Content based image retrieval consists of three parts: feature extraction, indexing and retrieval part. The techniques which are used to extract features of an image are called feature extraction techniques. The choice of features plays an important role in image retrieval. Some of the features used are color, texture and shape. Combination of these features provides better performance than single feature. Here we are extracting color and texture features with the proposed method consists of HMMD (Hue Min Max Difference) color plane and HDWT (Hadamard Discrete Wavelet Transform) techniques. It is proved in research work that HMMD HDWT reduced the size of feature vectors, storage space and gives high performance than intensity-Haar, RGB-Haar and RGB-HDWT.

Authors and Affiliations

Deshbir Singh, Sandeep Kaur

Keywords

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  • EP ID EP22712
  • DOI -
  • Views 252
  • Downloads 4

How To Cite

Deshbir Singh, Sandeep Kaur (2016). Content-Based Image Retrieval using HSV and Hadamard DWT. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 4(10), -. https://europub.co.uk/articles/-A-22712