Image retrieval using local frequency maxima of histogram based color Correlogram

Image retrieval using local frequency maxima of histogram based color Correlogram

Color histograms is a very useful technique used for retrieving and indexing images in a content-based image retrieval (CBIR) system. They provide a graphical representation of global color distribution of an image. However, the histograms are not robust to major changes in the object appearance. There might also be a case where histogram might give same or similar representation for different images, which depends upon the color distribution in the images. Correlograms are used for efficient indexing of images. They not only extract the color distribution of pixels in images like color histogram, but also extracts the spatial information of pixels in the images. The characteristic of the intensity Correlogram are taken into account for extracting the spatial information as well as the distribution of color pixels greatly attracts the researcher for content based image retrieval. In this paper, we propose the image bin (histogram value divisions) separation technique followed by extracting maxima of frequencies and plotting a Correlogram. At first, the histogram is calculated for an image. After that, it is subdivided into four equal bins. Each bin is subdivided into four more bins and for every such subdivision the maxima of frequencies is calculated. This information is stored in the form of a Correlogram. The distance between Correlogram of the query image and the corresponding Correlogram of database images is calculated. The proposed algorithm is tested on a database comprising a large number of images and gives promising results.

Color histograms is a very useful technique used for retrieving and indexing images in a content-based image retrieval (CBIR) system. They provide a graphical representation of global color distribution of an image. However, the histograms are not robust to major changes in the object appearance. There might also be a case where histogram might give same or similar representation for different images, which depends upon the color distribution in the images. Correlograms are used for efficient indexing of images. They not only extract the color distribution of pixels in images like color histogram, but also extracts the spatial information of pixels in the images. The characteristic of the intensity Correlogram are taken into account for extracting the spatial information as well as the distribution of color pixels greatly attracts the researcher for content based image retrieval. In this paper, we propose the image bin (histogram value divisions) separation technique followed by extracting maxima of frequencies and plotting a Correlogram. At first, the histogram is calculated for an image. After that, it is subdivided into four equal bins. Each bin is subdivided into four more bins and for every such subdivision the maxima of frequencies is calculated. This information is stored in the form of a Correlogram. The distance between Correlogram of the query image and the corresponding Correlogram of database images is calculated. The proposed algorithm is tested on a database comprising a large number of images and gives promising results.