Optical feature extraction using the Radon transform and angular correlation

Oodaye B. Shukla; Bradley G. Boone

doi:10.1117/12.140916

12 January 1993 Optical feature extraction using the Radon transform and angular correlation

Oodaye B. Shukla, Bradley G. Boone

Proceedings Volume 1772, Optical Information Processing Systems and Architectures IV; (1993) https://doi.org/10.1117/12.140916
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

This paper describes two processing algorithms that can be implemented optically: the Radon transform and angular correlation. These two algorithms can be combined in one optical processor to extract all the basic geometric and amplitude features from objects embedded in video imagery. We show that the internal amplitude structure of objects is recovered by the Radon transform, which is a well-known result, but, in addition, we show simulation results that calculate angular correlation, a simple but unique algorithm, which extracts object length, width, area, aspect ratio, orientation and boundary from suitably thresholded images. In addition to being insensitive to scale and rotation, these simulations indicate that the features derived from angular correlation algorithm are relatively insensitive to tracking shifts and image noise. Some optical architecture concepts, including one based on micro-optical lenslet arrays, have been developed to implement these algorithms. We will discussed these architectures, stressing the micro-optical approach. Test and evaluation using simple synthetic object data will be described. We will also describe the results of a study that uses object boundary (derivable from angular correlation) to classify objects using a neural network.

Citation Download Citation

Oodaye B. Shukla and Bradley G. Boone "Optical feature extraction using the Radon transform and angular correlation", Proc. SPIE 1772, Optical Information Processing Systems and Architectures IV, (12 January 1993); https://doi.org/10.1117/12.140916

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