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Enhancement of Color Image Retrieval using Adaptive Texture Descriptor
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 178 - Number 32 |
| Year of Publication: 2019 |
| Authors: Disha Sugha, Honeyily, Vinay Thakur |
10.5120/ijca2019919188
|
Disha Sugha, Honeyily, Vinay Thakur . Enhancement of Color Image Retrieval using Adaptive Texture Descriptor. International Journal of Computer Applications. 178, 32 ( Jul 2019), 35-38. DOI=10.5120/ijca2019919188
Abstract
Objective of finding digital images from large database various methods of computer vision techniques of image retrieval are there, out of which Content Based Image Retrieval (CBIR) is widely used. Modern image retrieval systems use content-based image retrieval, as there is increased demand of images in digital format. Nowadays, the latest technique used for image retrieval is content based image retrieval. In digital image processing CBIR is rapidly growing field. In content-based image retrieval method, retrieval of image requires various visual features of image, like- color, shape, texture, etc; so that desired image could be retrieved as per the requirement of user. On the other hand, if we talk about retrieval of image manually from huge set of databases, is time-consuming, laborious and expensive as compared to content-based image retrieval. Therefore, to reduce time for image retrieval we prefer CBIR. In this paper, technique for content-based image retrieval includes texture of data image which is used to calculate energy, contrast and time elapsed of an image using adaptive texture descriptor method. Hence, to increase the enhancement of image, number of features increased for comparison with previous work and value of parameters are also calculated for comparative analysis and on comparing features with stored database time elapsed is also calculated.
References
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