The traditional Otsu algorithm has to exhaustively compute all between-class variances.Based on one characteristic of Otsu threshold

this paperwork proposes a new fast algorithm.The new algorithm finds out every threshold which is equal to the integer part of the average of the mean levels of two classes

and then selects one threshold which is in accord with Otsu criterion.The traditional Otsu algorithm cannot work well when it extracts small object from gradient image

so an improved thresholding algorithm is proposed.Based on the fast Otsu algorithm provided

the improved thresholding algorithm recursively computes threshold.Experimental results show that the fast Otsu algorithm is faster than the traditional Otsu algorithm. Experimental results also show that the improved thresholding algorithm is effective to segment small object of gradient image.