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Survey Paper on Content Based Image Retrieval

Author(s):

Rahul Moriwal , AITR INDORE

Keywords:

Image Retrieval, Clustering, Wavelet Transform, HaarWavelet Transform, Feature Extraction, K-Means Technique

Abstract

The content based image retrieval (CBIR) is the well-liked and heart favorite area of research in the field of digital image processing. The key goal of content based image retrieval (CBIR) is to excerpt the visual content of an image directly, like color, texture, or shape. There are several applications of the CBIR technique such as forensic laboratories, crime detection, image searching etc. For the purpose of feature extraction of well-matched images from the database, a universal CBIR system utilizes texture, color and shape based techniques. In this presented work, we have offered an efficient approach for the content based image retrieval, where images are decomposed using the wavelet transform, it means that the image features are converted in the matrix form and a color feature data set is prepared. In order to improve search results we have used k-means algorithm. It is shown by experimental results that, the efficiency of the proposed method is improved in contrast with the existing method.

Other Details

Paper ID: IJSRDV7I70139
Published in: Volume : 7, Issue : 7
Publication Date: 01/10/2019
Page(s): 190-193

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