Fast and efficient indexing approach for object recognition

Alaa Hefnawy; Samia A. Mashali; Mohsen Rashwan; Magdi Fikri

doi:10.1117/12.360311

26 August 1999 Fast and efficient indexing approach for object recognition

Alaa Hefnawy, Samia A. Mashali, Mohsen Rashwan, Magdi Fikri

Proceedings Volume 3837, Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision; (1999) https://doi.org/10.1117/12.360311
Event: Photonics East '99, 1999, Boston, MA, United States

Abstract

This paper introduces a fast and efficient indexing approach for both 2D and 3D model-based object recognition in the presence of rotation, translation, and scale variations of objects. The indexing entries are computed after preprocessing the data by Haar wavelet decomposition. The scheme is based on a unified image feature detection approach based on Zernike moments. A set of low level features, e.g. high precision edges, gray level corners, are estimated by a set of orthogonal Zernike moments, calculated locally around every image point. A high dimensional, highly descriptive indexing entries are then calculated based on the correlation of these local features and employed for fast access to the model database to generate hypotheses. A list of the most candidate models is then presented by evaluating the hypotheses. Experimental results are included to demonstrate the effectiveness of the proposed indexing approach.

Citation Download Citation

Alaa Hefnawy, Samia A. Mashali, Mohsen Rashwan, and Magdi Fikri "Fast and efficient indexing approach for object recognition", Proc. SPIE 3837, Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision, (26 August 1999); https://doi.org/10.1117/12.360311

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