The week's pick
Random Articles
Reseach Article
Content based Image Retrieval (CBIR) System using Threshold based Color Layout Descriptor (CLD) and Edge Histogram Descriptor (EHD)
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 179 - Number 41 |
| Year of Publication: 2018 |
| Authors: Pradnya A. Vikhar, P. P. Karde |
10.5120/ijca2018916985
|
Pradnya A. Vikhar, P. P. Karde . Content based Image Retrieval (CBIR) System using Threshold based Color Layout Descriptor (CLD) and Edge Histogram Descriptor (EHD). International Journal of Computer Applications. 179, 41 ( May 2018), 39-43. DOI=10.5120/ijca2018916985
Abstract
The accuracy of any Content Based Image Retrieval (CBIR) system is depend on the accuracy of features extracted from the images. Therefore feature extraction is the first and most important step to develop the CBIR system. Instead of using single feature, most common CBIR system uses combination of color, texture and/or shape to accurately represent an image. MPEG-7 feature extraction provides standards set of descriptors to represent the images and are widely used in many applications. In this paper the concept and area of content based image retrieval system is introduced first. Further it covers the overview of basic MPEG-7 visual feature descriptor; CLD (Color Layout Descriptor) and edge histogram descriptor (EHD) to extract the contents from images. To reduce the overall searching process the advancement in CLD and EHD is suggested by introducing the concept of thresholding.
References
- Suman Lata, Parul Preet Singh, “A Review on Content Based Image Retrieval System”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 5, PP 561-566, May 2014
- Shereena V.B, Julie M. David, “Content Based Image Retrieval: A Review”, Computer Science & Information Technology, Computer Science Conference Proceedings (CSCP), pp. 65–77, 2014
- Vikhar Pradnya A. "Content-Based Image Retrieval (CBIR): State-of-the-Art and Future Scope for Research", IUP Journal of Information Technology, Vol. 6,Issue 2, pp. 64-84, June 2010
- Shiv Raj Singh, Dr. Shruti Kohli”, Enhanced CBIR using Color Moments, HSV Histogram, Color Auto Correlogram, and Gabor Texture”, International Journal of Computer Systems (ISSN: 2394-1065), Volume 02– Issue 05, pp 161-165, May, 2015
- Jun Zhang, Lei Ye, and Jianhua Ma, “MPEG-7 Visual Descriptors and Discriminant Analysis”, The Handbook of MPEG Applications: Standards in Practice, John Wiley & Sons Ltd, 2011
- Laila Shoukry, Sebastian Klenk, Gunther Heidemann, “MPEG-7 Feature Visualization for CBIR Systems”, in proceedings of International Conference on Computer Theory and Applications (ICCTA 2010), 2010
- Pradnya Vikhar, Pravin Karde, “Improved CBIR System using Edge Histogram Descriptor (EHD) and Support Vector Machine (SVM)”, IEEE International Conference on ICT in Business Industry & Government (ICTBIG), April 2017.
- M H Saad, H I Saleh, H Konbor, M Ashour, “Image Retrieval based on Integration between YCbCr Color Histogram and Shape Feature”, IEEE Computer Engineering Conference (ICENCO), 2011, vol., no., pp.97-102, 27-28, 2012
- Ching-Hung Sua, Mohd Helmy Abd Wahab and Tsai-Ming Hsieh, “Image Retrieval based on color and texture features”, IEEE 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2012), PP 1816-1819, 2012.
Index Terms
Keywords