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Image distance transforms that use optical correlation

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Abstract

The image distance transform is a time-consuming global operation. We use optical correlation for the fast computation of binary image distance transforms. A joint transform correlator is proposed to implement the algorithm that accommodates the morphological threshold-decomposition concept. The proposed optical processor is programmable for computing Euclidean, city-block, and chessboard distance transforms in real time. Skeletonization by use of the distance transform and the rotation invariance of the Euclidean distance transform are demonstrated.

© 2000 Optical Society of America

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