In the recent past, research in the field of automatic sign language recognition using
machine learning methods have demonstrated remarkable success and made momentous …

Abstract Evaluation and benchmarking of real-time skin detectors remain challenging
because of multiple evaluation attributes that must be considered. Numerous evaluation and …

Sign language recognition system (SLRS) is one of the application areas of human
computer interaction (HCI) where signs of hearing impaired people are converted to text or …

In this paper, we introduce a new self-adaptive algorithm for segmenting human skin regions
in color images. Skin detection and segmentation is an active research topic, and many …

Sign Language (SL) is the main language for handicapped and disabled people. Each
country has its own SL that is different from other countries. Each sign in a language is …

This paper presents a new method for skin region segmentation based on a zero-sum game
theory model which exploits the opposite classifications of an image region by different skin …

An individual's privacy is a significant concern in surveillance videos. Existing research work
into the location of individuals on the basis of detecting their skin is focused either on …

This paper presents a novel rule-based skin detection method that works in the YCbCr color
space. The method is based on correlation rules that evaluate the combinations of …

The use of deep-learned features has recently allowed for improving the performance of skin
detection and segmentation. In particular, fully-convolutional U-Nets, proposed for …

This paper presents a survey of blob detection methods which has been applied on image
processing with relation of medical images proposed by literature.“The blob detection is a …