AFast polynomial fits sub-pixel edge detection algorithms

Since traditional edge detection algorithms have the disadvantages of low precision and efficiency in measuring the edge, a sub-pixel edge detection algorithm based on the polynomial fittings is proposed. According to the grey level distribution of the picture, this algorithm uses cubic polynomial to fit the edges to realize sub-pixel localization. Traditional sub-pixel edge detection algorithms detect coarse position at first, and then carry out the sub-divide, therefore the running time is relatively long. This method first fetches some points near the edge, and then carries out the sub-pixel edge detection algorithm, so the running time is reduced. Finally, the experimental results show that the proposed algorithm is very reliable and efficient.