Proceedings Article | 13 May 2019
KEYWORDS: Skin, Binary data, RGB color model, Facial recognition systems, Video, Image processing, Machine learning, Image analysis, Human-computer interaction, Neural networks
Region growing is defined as a procedure of finding regions containing user defined objects of interest. Growing region is a vital phase for various image processing applications. Growing region in images has been very challenging as it is the base for further image analysis, interpretation, and classification. Region growing varies for different purpose of aim. However, the identified region are widely used for various domain-skin detection, detect object in image, hand gesture detection, etc. In this paper, the main concentration is to defining region of interest from an image based on skin detection. A clustering method was used. Skin detection can be used as a preprocessing step for several applications included but not limited to various Human Computer Interaction (HCI) tasks. However, skin detection is a challenging problem due to sparse variations of skin tone of human. Skin tone can be confused with background color, attire color, ethnicity, individual characteristics-age, sex, body parts, makeup, hair color, presence of non-human objects, and camera calibration. Besides that, lightning conditions also plays a vital role. Researchers have been working tirelessly for an efficient skin detection method but those are not beyond limitations. Various approach including pixel wise threshold for various color spaces, segmentation, face and hand detection based approaches are proposed. But it still lacks from a method which can be applied for all types of skin detection. In this paper, a novel skin detection method is proposed which is free from any manual threshold values and automatically define number of clusters.
