A Comparative Study on Retrieved Images by Content Based Image Retrieval System based on Binary Tree, Color, Texture and Canny Edge Detection Approach

Content based image retrieval (CBIR) is a technique in which images are indexed by extracting their low level features or high level features or both. This paper presents performance & comparative study of the result obtained by the two different approaches of CBIR system. The resultant retrieved images by the CBIR system is based on two approaches. Both approaches of the system using two major processes one as feature extraction and other as search and retrieval. The first approach is based on extracting the features using binary tree structure, color & texture and the second approach is based on extracting shape features using Canny Edge Detection. In both the approaches the feature vector of the query image is compared with the feature vector of the each image present in the database. In the first approach the images are retrieved and arranged according to their matching score or rank value and in the second approach retrieved images are arranged according to their mean and correlation values.

@article{Shambharkar2012,
  title     = {A Comparative Study on Retrieved Images by Content Based Image Retrieval System based on Binary Tree, Color, Texture and Canny Edge Detection Approach},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {2},
  number    = {1},
  year      = {2012},
  publisher = {The Science and Information Organization},
  note      = {Special Issue on Selected Papers from International Conference & Workshop On Emerging Trends In Technology 2012},
  author    = {Saroj A Shambharkar and Shubhangi C. Tirpude},
  doi       = {10.14569/SpecialIssue.2012.020106},
  url       = {https://doi.org/10.14569/SpecialIssue.2012.020106}
}