Skin detection is used in applications ranging from face detection, tracking body parts and hand gesture analysis, to retrieval and blocking objectionable content. We present a systematic approach for skin segmentation with graph cuts by using local skin information, universal skin information and skin augmentation using the off-line learned model. The skin segmentation process starts by exploi...

The extraction of the skin pixels in a human image and rejection of non-skin pixels is called the skin segmentation. Skin pixel detection is the process of extracting the skin pixels in a human image which is typically used as a pre-processing step to extract the face regions from human image. In past, there are several computer vision approaches and techniques have been developed for skin pixe...

Human skin detection is the main task for various human–computer interaction applications. For this, several computer vision-based approaches have been developed in recent years. However, different events and features can interfere segmentation process, such as luminosity conditions, tones, complex backgrounds, image capture equipment. In digital imaging, methods overcome these challenges or at...

Skin lesion can be deadliest if not detected early. Early detection of skin save many lives. Artificial Intelligence and Machine learning is helping healthcare in ways so the diagnosis lesion. Computer aided help clinicians detecting cancer. The study was conducted to classify seven classes using very powerful convolutional neural networks. two pre trained models i.e DenseNet Incepton-v3 were e...

This paper addresses a problem of skin segmentation for sign language recognition purposes. The main contributions of the presented research is an adaptive skin model enhanced with a blob analysis algorithm which significantly improves skin detection effectiveness. Adaptive skin detector utilizes a statistical skin color model updated dynamically based on a face region defined by eye positions....