A robust skin detector is the primary need of many fields of computer vision, including face detection, gesture recognition, and pornography filtering. Less than 10 years ago, the first paper on automatic pornography filtering was published. Since then, different researchers claim different color spaces to be the best choice for skin detection in pornography filtering. Unfortunately, no compreh...

One of the difficult problems recognized in image processing and pattern analysis, in particular in medical imaging applications is boundary detection. The detection of skin lesion boundaries accurately allows, skin cancer detection .There is no unified approach to this problem, which has been found to be application dependent. Early diagnosis of melanoma is a challenge, especially for general ...

Skin cancer is the most common type of cancer and there are two forms: melanomas and melanoma (basal cell carcinoma and squamous cell carcinoma). The main risk factor in both types of skin cancer is exposure to sunlight and other sources of ultraviolet radiation. In comparison with basal or squamous cell carcinoma melanoma skin cancer is less common but more serious if not treated early, and ca...

Techniques for color-based tracking of faces or hands often assume a static skin color model. However, skin color perceived by a camera can change when lighting changes. In common real environment multiple light sources impinge on the skin. Therefore, for robust skin pixel detection, a dynamic skin color model that can cope with the changes must be employed. We show that skin detection in video...

Color is one of the most prominent features of an image and used in many skin and face detection applications. Color space transformation is widely used by researchers to improve face and skin detection performance. Despite the substantial research efforts in this area, choosing a proper color space in terms of skin and face classification performance which can address issues like illumination ...

Pollution, an unhealthy lifestyle, UV radiation, and other factors can contribute to skin cancer. A variety of machine learning techniques have been developed in the past detect such malignancies before they worsen. The goal this article is utilize a convolutional neural network segment lesion images. purpose study see how deep may be utilized photos. People discover what diseases have, protect...

Skin segmentation is the process of the identifying the skin pixels in a image in a particular color model and dividing the images into skin and non-skin pixels. It is the process of find the particular skin of the image or video in a color model. Finding the regions of the images in human images to say these pixel regions are part of the image or videos is typically a preprocessing step in ski...

Face detection is one of the most useful research topics in computer vision. In the past several decades, there has been noticeable and successful achievement in face detection. However, it is still a challenge to obtain both low computational complexity and high detection efficiency. The main problem in existing skin color based face detection algorithms is that different illumination conditio...

Skin detection is the process of finding skin-colored pixels and regions in an image or a video. This process is typically used as a preprocessing step to find regions that potentially have human faces and limbs in images. Several computer vision approaches have been developed for skin detection. A skin detector typically transforms a given pixel into an appropriate color space and then use a s...