1 October 1997 Two-dimensional shape recognition using oriented-polar representation
Neng-Chung Hu, Kuo-Kan Yu, Yung-Li Hsu
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To deal with such a problem as object recognition of position, scale, and rotation invariance (PSRI), we utilize some PSRI properties of images obtained from objects, for example, the centroid of the image. The corresponding position of the centroid to the boundary of the image is invariant is spite of rotation, scale, and translation of the image. To obtain the information of the image, we use the technique similar to Radon transform, called the oriented-polar representation of a 2-D image. In this representation, two specific points, the centroid and the weighted mean point, are selected to form an initial ray, then the image is sampled with N angularly equispaced rays departing from the initial rays. Each ray contains a number of intersections and the distance information obtained from the centroid to the intersections. The shape recognition algorithm is based on the least total error of these two items of information. Together with a simple noise removal and a typical backpropagation neural network, this algorithm is simple, but the PSRI is achieved with a high recognition rate.
Neng-Chung Hu, Kuo-Kan Yu, and Yung-Li Hsu "Two-dimensional shape recognition using oriented-polar representation," Optical Engineering 36(10), (1 October 1997). https://doi.org/10.1117/1.601511
Published: 1 October 1997
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Cited by 6 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Signal to noise ratio

Chromium

Neural networks

Binary data

Distance measurement

Image processing

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