Research on recognition of work-piece based on improved SIFT algorithm

Efficiency image matching technology is very important to assembly product line based on machine vision. SIFT (scale invariant feature transform) descriptor is commonly used in image matching because of the good invariance of scale, rotation, illumination. But its algorithm is complicated and computation time is long. To improve SIFT algorithm real-time quality, the method of reducing similar measure matching cost is mentioned. Euclidean distance is replaced by the linear combination of cityblock distance and chessboard distance, and reduce character point in calculating with results of part feature. The work-piece recognition experimental results show that the algorithm can reduce the rate of time complexity and maintain robust quality at the same time, image matching efficiency is improved.