A slope fitting corner detection algorithm based on edge chain-code
The corner points in an image provide key information for describing object features.Corner detection is the pre-pro-cessing step for complex image applications,and its quality directly affects the effectiveness of subsequent steps.In industrial environment,corner detection often requires real-time,accurate and efficient processing on large-scale image dataset while facing various types of noise and interference,so design high efficient corner detection algorithm is significantly important in prac-tice.Focusing on the limitations of traditional corner detection algorithms that require curvature calculation or curve fitting,a fast and light-weight method based on Freeman chain coded edge points was proposed,and whether the edge point was corner could be determined by slope fitting on multiple consecutive points before and after the current edge point and threshold on the includ-ed angle.The simulations were conducted in NRS industrial image dataset,its performances were evaluated in terms of accuracy,robustness,and speed,as compared with traditional algorithms such as HARRIS,SUSAN and SIFT,etc.The results showed that the proposed algorithm had fewer false positives and negatives with faster detection speed,exhibiting more superiority in indus-trial applications.
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