Color Object Detection Based Image Retrieval Using ROI Segmentation with Multi-Feature Method-Reference-Cited by-同舟云学术

Color Object Detection Based Image Retrieval Using ROI Segmentation with Multi-Feature Method

Published:2020-01-01 Issue:1 Volume:112 Page:169-192
ISSN:0929-6212
Container-title:Wireless Personal Communications
language:en
Short-container-title:Wireless Pers Commun

Author:

Raja Rohit^ORCID,Kumar Sandeep,Mahmood Md Rashid

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Computer Science Applications

Link

http://link.springer.com/content/pdf/10.1007/s11277-019-07021-6.pdf

Reference18 articles.

1. Arya, D., & Jha, J. (2016) Global and local descriptor for CBIR and image enhancement using multi-feature fusion method. International Journal of Research—GRANTHAALAYAH.

2. Agarwal, S., Verma, A. K., & Dixit, N. (2011). Content-based image retrieval using color edge detection and discrete wavelet transform. In International conference on issues and challenges in intelligent computing techniques (ICICT), February 7–8, 2011 (pp. 368–372)

3. Zinzuvadia, K. M., Tanawala, B. A., & Brahmbhatt, K. N. (2015). A survey on feature-based image retrieval using classification and relevance feedback techniques. IJIRCCE,2, 1253.

4. Dixit, N., Tiwari, S. K., & Sharma, P. (2016). A new algorithm for CBIR using bi-cubic interpolation with color coding and different level DWT. In 2016 IEEE (ICCUBEA) (pp. 1–6).

5. Kaur, M., & Dhingra, S. (2017). Comparative analysis of image classification techniques using statistical features in CBIR systems. In I-SMAC 2017 (pp. 265–270). IEEE.

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