CBIR : Color Feature Extraction using CIELAB Color Space with Compact Color Signature
N. Parvin1, P. Kavitha2

1N. Parvin*, Research Scholar, Periyar University, Salem, Tamil Nadu, India.
2Dr.P.Kavitha, Department of Computer Science, Paavendhar College of Arts and Science, M.V. South, Attur. Tamil Nadu, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 27, 2020. | Manuscript published on April 10, 2020. | PP: 470-476 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3770049620/2020©BEIESP | DOI: 10.35940/ijitee.F3770.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The immense progress of new technology we have been created an enormous number of digital images by using such devices as a digital camera, scanner, and mobile phones so on. All the images which are taken by the devices to keep in Image Database. For retrieving the desire images which were given in an input image has compared with the large database according to the visual content used by the technique as referred to as the Content Based Image Retrieval (CBIR) system. There are two phases for retrieving images in the CBIR system, as the first one is feature extraction and the second one is similarity size. Thus, the feature extraction consists of every image has produced symbolic content in the form of the function. The visual contents of an image in the CBIR system contain the features which have represented as shape, texture, spatial region and color of the images. In our paper tries to design the images’ color features as in the steps to focus color representation in the k-d tree, CIELAB color space of color signature compression along with categories of Human’s color for Content-based image retrieval and also acquire the results using MATLAB. 
Keywords: CBIR, CIELAB, Digital Images, Feature Extraction, k-d tree.
Scope of the Article: Smart Spaces