Image retrieval using wavelet transform and shape decomposition

Authors:
Yen Do;Soo Hyung Kim;In Seop Na;Dae Wook Kang;Jin Hyung Kim
Affiliations:
Chonnam National University, YongBong-ro, Korea;Chonnam National University, YongBong-ro, Korea;Chonnam National University, YongBong-ro, Korea;Chonnam National University, YongBong-ro, Korea;Korea Advanced Institute Science and Technology, Daejeon, Korea
Venue:
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
Year:
2013

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Abstract

In this paper, we propose an image retrieval system that uses both local and global shape features to retrieve the most similar images from the database. To obtain both features, some pre-processing steps, such as object segmentation using Minimum Error Thresholding and border extraction, are firstly carried out. After that, the Grid Based method is used to extract the global shape feature. The system divides the image into smaller areas and extracts local features by applying discrete wavelet transform and singular value decomposition. Finally, we compute the similarities between the global and local features of the query image and all the images in the database to give the most possible candidate matches as a result. The experimental results show the strengths and effectiveness of the proposed system.