Image retrieval with rotation invariance

• Published in: 2011 3rd International Conference on Electronics Computer Technology Vol. 2; pp. 194 - 198
• Main Authors: Sekhar, P. N. R. L. Chandra, Prasad, P. Surya, Kumar, M. Vinodh, Santosh, D. Hari Hara
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2011
• Subjects: Feature extraction; feature vector; Image color analysis; Image retrieval; Image segmentation; Rotation Invariance; Shape; Similarity check; Texture features; Transforms
• DOI: 10.1109/ICECTECH.2011.5941683
• ISBN: 1424486785; 9781424486786

The enormous increase in the image database sizes, as well as its vast development in various applications, retrieval of images based on its content is an important research area with application to digital libraries and multimedia databases. Content Based Image Retrieval (CBIR) is one of the methods which use low level features like color, texture and shape information to retrieve the images. Effective texture feature is an essential component in any content based image retrieval systems in which Curvelet captures the texture features more efficiently than other spectral features like Gabor and wavelet. This paper describes an approach to achieve a rotation invariant CBIR by using Curvelet texture feature and make them into different segments of similar groups to improve the efficiency of retrieval. Combine all these features into a feature vector and retrieve the similar images based on similarity check. This approach gives better results even for the images found in different orientations.