Adaptive Thresholding for Skin Lesion Segmentation Using Statistical Parameters

摘要

Melanoma is one of those skin cancers whichcan be fatal. So, the segmentation of lesions from the digitalimages becomes a crucial step in analysis and diagnosis of askin cancer using image processing techniques. This workproposes a technique for automatic segmentation of lesionfrom the digital dermoscopic images using adaptive thresholdmaking the process invariant and robust. The statisticalfeatures like standard deviation and mean are used topreprocess and segment the lesions completely in an automaticmanner. The use of image processing techniques, such asaverage filtering for removal of hair and skin scales, mathematical morphology to reject the false positives havebeen successfully able to accurately segment the lesion fromthe images. The results are significant and indicate that themethod has good accuracy. An average correlation of 90% andaverage overlapping score of 83% has been obtained.