This work describes an implementation for skin detection which relies on the H channel to characterize the skin colors range. The openCv library is used for image processing. The program initially converts RGB images to HSV one. The H channel is used to characterize the colors range for skin detection. To illustrate the approach we compare this with others.

A short review of the recent status of optical biopsy of human skin as a tool for cutaneous tumour detection will be presented. Basically laserand lightinduced fluorescence and diffuse reflectance techniques incorporated in so called “optical biopsy” technique used for skin tissue analysis will be described and some original results and findings from our own investigations will be commented as ...

Bovine mastitis (BM) is a prevalent condition on dairy farms, affecting both livestock health and reducing profitability. This study investigated the feasibility of diagnosing BM in Holstein dairy cattle using thermography. To increase the detection between healthy cattle and unhealthy one and to better compare the results from thermal images, a number of parameters including somatic cell count...

Convolutional Neural Networks have demonstrated human-level performance in the classification of melanoma and other skin lesions, but evident disparities between differing tones should be addressed before widespread deployment. In this work, we propose an efficient yet effective algorithm for automatically labelling tone lesion images, use to annotate benchmark ISIC dataset. We subsequently the...