Image Threshold Detection and Granularity Analysis Algorithm Based on FLOM

To detect the tiny sclerotic tissues in pathological examination,the α stable distribution and the fractional lower order statistics (FLOS) (i.e. fractional lower order moment,FLOM) are introduced. The threshold detection method based on FLOS under the non-Gaussian condition,the definition of the granularity distribution function and the autocorrelation moment are proposed as well. Firstly,taking the supersonic medical image as an example,the method based on Gaussian distribution and the α stable distribution method respectively to carry on the threshold detection for the supersonic medical image are discussed. After the detection,mathematics morphology is applied to calculate granularity distribution function of the horizontal direction and the vertical direction respectively. At last,the correlation coefficients of two directions are obtained. The experimental results show the threshold detection and granularity analysis method based on the fractional lower order statistics has its superiority.