Paper
20 December 1999 Image indexing using edge orientation correlogram
Jamshid Shanbehzadeh, Fariborz Mahmoudi, Abdolhosain Sarafzadeh, Amir Masoud Eftekhary Moghadam, Zahra Asarzadeh
Author Affiliations +
Proceedings Volume 3964, Internet Imaging; (1999) https://doi.org/10.1117/12.373444
Event: Electronic Imaging, 2000, San Jose, CA, United States
Abstract
One of the requirements for the fast growing technology of multimedia and Internet is image retrieval. A retrieval scheme needs to be efficient, and effective in finding similar images. This requires a robust retrieval scheme against rotation, reflection, translation, scaling, illumination and noise with low computational cost. In this paper a new scheme which overcomes the problems of previous retrieval systems such as sensitivity to illumination, false edges, translation, rotation, noise is introduced. The computational cost of this method is comparable to the previous methods. In this new scheme the image edges will be extracted first, then the edge angles are quantized. Based on correlation between amplitude and phase of neighboring edges the edge orientation correlogram, which is a 2D matrix, is generated. This matrix is normalized and ordered in such a wy that it becomes invariant to rotation, reflection, scaling and translation. This matrix can be used as a feature vector for describing the image and also as an index in image databases. The experimental result shows this new method is superior to other color-based, color-spatial and shape-based indexing schemes.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jamshid Shanbehzadeh, Fariborz Mahmoudi, Abdolhosain Sarafzadeh, Amir Masoud Eftekhary Moghadam, and Zahra Asarzadeh "Image indexing using edge orientation correlogram", Proc. SPIE 3964, Internet Imaging, (20 December 1999); https://doi.org/10.1117/12.373444
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Cited by 6 scholarly publications.
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KEYWORDS
Image retrieval

Databases

Image processing

Internet

Image segmentation

Multimedia

Content based image retrieval

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