A high-speed comer detection algorithm based on fuzzy ID3 decision tree was proposed. In the algorithm, the Bresenham circle with 3-pixel radius was used as the test mask, overlapping the candidate comers with the nuc...A high-speed comer detection algorithm based on fuzzy ID3 decision tree was proposed. In the algorithm, the Bresenham circle with 3-pixel radius was used as the test mask, overlapping the candidate comers with the nucleus. Connected pixels on the circle were applied to compare the intensity value with the nucleus, with the membership function used to give the fuzzy result. The pixel with maximum information gain was chosen as the parent node to build a binary decision tree. Thus, the comer detector was derived. The pictures taken in Fengtai Railway Station in Beijing were used to test the method. The experimental results show that when the number of pixels on the test mask is chosen to be 9, best result can be obtained. The comer detector significantly outperforms existing detector in computational efficiency without sacrificing the quality and the method also provides high performance against Poisson noise and Gaussian blur.展开更多
基金Project(J2008X011) supported by the Natural Science Foundation of Ministry of Railway and Tsinghua University,China
文摘A high-speed comer detection algorithm based on fuzzy ID3 decision tree was proposed. In the algorithm, the Bresenham circle with 3-pixel radius was used as the test mask, overlapping the candidate comers with the nucleus. Connected pixels on the circle were applied to compare the intensity value with the nucleus, with the membership function used to give the fuzzy result. The pixel with maximum information gain was chosen as the parent node to build a binary decision tree. Thus, the comer detector was derived. The pictures taken in Fengtai Railway Station in Beijing were used to test the method. The experimental results show that when the number of pixels on the test mask is chosen to be 9, best result can be obtained. The comer detector significantly outperforms existing detector in computational efficiency without sacrificing the quality and the method also provides high performance against Poisson noise and Gaussian blur.
