Title :
A reliable skin mole localization scheme
Author :
Cho, Taeg Sang ; Freeman, William T. ; Tsao, Hensin
Author_Institution :
Massachusetts Inst. of Technol., Cambridge
Abstract :
Mole pattern changes are important cues in detecting melanoma at an early stage. As a first step to automatically register mole pattern changes from skin images, this paper presents a framework to detect and label moles on skin images in the presence of clutter, occlusions, and varying imaging conditions. The input image is processed with cascaded blocks to successively discard non-mole pixels. Our method first searches the entire input image for skin regions using a non-parametric skin detection scheme, and the detected skin regions are further processed using a difference of Gaussian (DoG) filter to find possible mole candidates of varying sizes. Mole candidates are classified as moles in the final stage using a trained support vector machine. To increase the mole classification accuracy, hair is removed if present on the skin image using steerable filters and a graphical model. The performance of the designed system is evaluated with 28 test images, and the experimental results demonstrate the effectiveness of the proposed mole localization scheme.
Keywords :
Gaussian processes; image classification; medical image processing; object detection; skin; support vector machines; Gaussian filter difference; mole classification accuracy; mole pattern changes; nonparametric skin detection scheme; reliable skin mole localization scheme; skin images; steerable filters; support vector machine; Filters; Hair; Image processing; Malignant tumors; Pixel; Registers; Skin; Support vector machine classification; Support vector machines; Torso;
Conference_Titel :
Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on
Conference_Location :
Rio de Janeiro
Print_ISBN :
978-1-4244-1630-1
Electronic_ISBN :
1550-5499
DOI :
10.1109/ICCV.2007.4409144