| 摘要 |
An object recognition method analyzes an imaged object based on its contour. Extracted contours are characterized by wavelets and slope sequence, and compared to sets of stored contours to recognize a known feature. If a match of sufficiently high confidence is not found, the image is distorted to simulate an incrementally different perspective of the imaged object, and the process of contour identification, characterization and comparison is repeated until a match of sufficiently high confidence is found. The cycle of image distortions allow two-dimensional images obtained from a monocular vision system to be analyzed for three-dimensional motion for optimal recognition performance.
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