Author(s): Manimala Singha | K.Hemachandran
Journal: Signal & Image Processing
ISSN 2229-3922
Volume: 3;
Issue: 1;
Start page: 39;
Date: 2012;
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Keywords: Image Retrieval | Color Histogram | Color Spaces | Quantization | Similarity Matching | Haar Wavelet | Precision and Recall.
ABSTRACT
The increased need of content based image retrieval technique can be found in a number of different domains such as Data Mining, Education, Medical Imaging, Crime Prevention, Weather forecasting, Remote Sensing and Management of Earth Resources. This paper presents the content based image retrieval, using features like texture and color, called WBCHIR (Wavelet Based Color Histogram Image Retrieval).The texture and color features are extracted through wavelet transformation and color histogram and the combination of these features is robust to scaling and translation of objects in an image. The proposed system has demonstrated a promising and faster retrieval method on a WANG image database containing 1000 general-purpose color images. The performance has been evaluated by comparing with the existing systems in the literature.
Journal: Signal & Image Processing
ISSN 2229-3922
Volume: 3;
Issue: 1;
Start page: 39;
Date: 2012;
VIEW PDF
DOWNLOAD PDF Original pageKeywords: Image Retrieval | Color Histogram | Color Spaces | Quantization | Similarity Matching | Haar Wavelet | Precision and Recall.
ABSTRACT
The increased need of content based image retrieval technique can be found in a number of different domains such as Data Mining, Education, Medical Imaging, Crime Prevention, Weather forecasting, Remote Sensing and Management of Earth Resources. This paper presents the content based image retrieval, using features like texture and color, called WBCHIR (Wavelet Based Color Histogram Image Retrieval).The texture and color features are extracted through wavelet transformation and color histogram and the combination of these features is robust to scaling and translation of objects in an image. The proposed system has demonstrated a promising and faster retrieval method on a WANG image database containing 1000 general-purpose color images. The performance has been evaluated by comparing with the existing systems in the literature.