Image Retrieval Using HSV-HDWT Hybrid Transformation Domain
- Deepika Sharma
- Dr.G.S. Brar
CBIR, HSV, HDWT, RGB, Color Model
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. Efficient image searching, browsing and retrieval tools are required by users from various domains, including remote sensing, fashion, crime prevention, publishing, medicine, architecture, etc. For this purpose, many general purpose image retrieval systems have been developed. In CBIR, images are indexed by their visual content. 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. Further, HSV color space model will be used to improve the feature extraction and improve the precision. At the end, results are presented to show the efficacy of the proposed method.
Deepika Sharma, Dr.G.S. Brar. "Image Retrieval Using HSV-HDWT Hybrid Transformation Domain".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.6, Issue 1, pp.342-347, URL :https://rjwave.org/ijedr/papers/IJEDR1801057.pdf
Volume 6 Issue 1
Pages. 342-347