||Basal cell carcinomas (BCCs) are more common in Taiwan and Singapore . The prevention and early detection are important to people’s health. Studies on Computer-aided diagnosis (CAD) have developed to assist diagnosis on skin cancers. CAD has the advantages of speed and objective outcomes.|
Hair removal is the first step for computerized analysis on lesion images. This thesis aims at improving the performance of a popular body hair removal method, DullRazor®, on our data images. Accuracy of the detection is crucial for the balance between removing hair and removing wrongly other skin features.
The performance of DullRazor® depends on the dimension of images, background skin color, and the thickness of hair. The features of most images are small in length and width, and contain light reflection in the center. In order to peak the performance for the data images of this thesis, it is necessary to look into the properties of parameters and modify the procedure according to the data images.
This thesis proposes the median filter method for the hair removal of the data images with light reflection in the center. To compare with DullRazor method fairly, this thesis also customizes the size and shape of the structure element of morphological closing and opening for the data images. Lastly, a generalized analog directional score is introduced to compare with the conventional digital one for reducing noise.
In summary, the median filter method performs better than the open-close method, thus better than the DullRazor method. However, the performance of hair detection is sensitive to the properties of the images. It is suggested to adjust some parameters when higher performance is required. The procedure of this thesis could serve as an example to fine-tune the parameters systematically.
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