Hand gesture recognition for human computer interaction

Abstract

A hand gesture recognition system provide a natural, innovative and modern way of non verbal communication. It has a wide area of application in human computer interaction and sign language. The intention of this paper is to discuss a novel approach of hand gesture recognition based on detection of some shape based features. The setup consist of a single camera to capture the gesture formed by the user and take this hand image as an input to the proposed algorithm. The overall algorithm divided into four main steps, which includes segmentation, orientation detection, feature extraction and classification. The proposed algorithm is independent of user characteristics. It does not require any kind of training of sample data. The proposed Implemented algorithm has been tested on 390 images, gives a recognition rate of approximately 92% and average elapsed time of 2.76 sec. It takes a less computation time as compare to other approaches.

Hand gesture recognition based on shape parameters

“…This is universal truth that every person poses almost same hand shape with one thumb and four fingers under normal condition. The success of approach discussed in paper [1] for hand gesture recognition based on shape features is highly influenced by some constraints like hand should be straight for orientation detection in image, if it will not be followed then result could be unexpected or wrong and also we fix the new parameter to detect the presence of thumb. In paper [2], the approach is based on calculation of three combined features of hand shape which are compactness, area and radial distance.…”

“…Compactness is the ratio of squared perimeter to area of the shape. If compactness of two hand shapes are equal then they would be classified as same, in this way this approach limits the number of gesture pattern that can be classified using these three shape based descriptors and only 10 different patterns have been recognized [1]. The algorithm implemented in this paper is divided into four main steps.…”

A Model for Real-Time Recognition and Textual Representation of Malaysian Sign Language through Image Processing

“…However, Jinda-apiraksa has discussed a basic technique to recognize three shape-based features of a hand to understand and interpret the meaning of gestures based on compactness and radial distance [13]. Whereas Panwar discusses a novel technique using shape based features to recognize the hand gestures using single camera [12].…”

“…In order to detect the direction of hands in an image, hand must be straight, so the outcome could be anticipated or correct [12]. However, Jinda-apiraksa has discussed a basic technique to recognize three shape-based features of a hand to understand and interpret the meaning of gestures based on compactness and radial distance [13].…”

A hand gesture recognition technique for human–computer interaction

“…These studies can be divided into two categories, based on their motion capture mechanism: vision-based or glove-based. Vision-based techniques rely on image processing algorithms to extract motion trajectory and posture information [8,9,10]. Their success highly depends on the used image analysis approaches, which are sensitive to the environmental factors, such as illumination changes, and may lose fine details due to hand and finger occlusion [11].…”