The week's pick
Reseach Article
Improving Efficiency of CBIR by using Color, Texture and Fusion Features with Bit Pattern
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 178 - Number 15 |
| Year of Publication: 2019 |
| Authors: Ramandeep Kaur, Vineet Khanna |
10.5120/ijca2019918877
|
Ramandeep Kaur, Vineet Khanna . Improving Efficiency of CBIR by using Color, Texture and Fusion Features with Bit Pattern. International Journal of Computer Applications. 178, 15 ( May 2019), 18-25. DOI=10.5120/ijca2019918877
Abstract
Digital graphic offers many advantages for processing and distributing image and other types of understanding. A single color image have more information of the different situations and object scenario and each color and texture have own characteristics. Geometrical and color information extraction are the key issue. CBIR finds and show images alike to one given as query image and another are similar images. In the earlier work, most of the researchers used low level features but there are some challenges like distortion of image, color imbalance, semantic gap between low level features etc. The challenges, be that as it may, is in planning a system with the capacity to retrieve best possible matches when there is an occurrence of all kind of images as query without using some other relevant information, for example, metadata, keywords and labels etc, and using only content of the images. The system proposed in this approach aim to retrieve the most relevant images using color, edge histogram descriptor with bitmap by using fusion based feature. Applications of the proposed system are climate forecast, crime prevention, military imaginary etc.
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