Image Retrieval Based on Contour and Relevance Feedback

Abstract:

In this paper an algorithm is proposed to retrieve images based on contour moment invariants of image and relevance feedback. Firstly, the contour of each query image is extracted and its contour moment invariant is computed. Then according to Euclid Distance between the query image and each image in the image database, the most similar images to the query image can be found. Finally, the relevance feedback algorithm based on support vector machine (SVM) is applied to improve retrieval precision. Experimental results show that the algorithm is more accurate and efficient to retrieve images with monotonous background and clear object and meet the invariance on shift, rotation and scale transform of objects.

• Periodical: Applied Mechanics and Materials (Volumes 182-183)
• Pages: 1771-1775
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.182-183.1771
• Online since: June 2012
• Authors: Wei Lu
• Keywords: CBIR, Contour Moment Invariants, Relevance Feedback, Support Vector Machine (SVM)

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