scholarly journals Hand gesture recognition using average background and logical heuristic equations

2013 ◽  
Vol 11 (5) ◽  
pp. 2634-2640
Author(s):  
Hazem Khaled Mohamed ◽  
S. Sayed ◽  
El Sayed Mostafa ◽  
Hossam Ali
Keyword(s):  
Convex Hull ◽  
Gesture Recognition ◽  
Background Subtraction ◽  
Reference Model ◽  
Region Of Interest ◽  
Recognition Algorithm ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Subtraction Technique ◽  
Heuristic Technique

This paper introduces a hand gesture recognition algorithm for Human Computer Interaction using real-time video streaming .The background subtraction technique is used to extract the ROI (Region Of Interest) of the hand. Fingertip is detected using logical heuristics equations that are applied on hand contour , convex hull and convexity defects points. A combination between background subtraction and logical heuristic technique that leads to more accurate results is introduced. Experimental results prove that the proposed algorithm improve the finger's tips detection by 52 % compared to the reference model.

scholarly journals Hand Gesture Recognition using Convexity Defect

2019 ◽  
Vol 9 (1) ◽  
pp. 1161-1165
Keyword(s):  
Feature Extraction ◽  
Gesture Recognition ◽  
Background Subtraction ◽  
Feature Recognition ◽  
Region Of Interest ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Smart Appliances ◽  
Rgb Values

Gestures are the simplest way of conveying a message, rather simpler than verbal means. It is the most primitive way of conversation. Gestures can also be the easiest and intuitive way of communicating with a computer, they can be used to communicate or convey information to computers, robots, smart appliances and many other pieces of machinery. It can eliminate the use of mouse and keyboard to some extent. The gestures cited are basically the variable positions as well as orientations of the hand. They can be detected by a simple webcam attached to the computer. The image is first changed into its corresponding RGB values and then to HSV values for better handling and feature recognition. The hand is segregated from the background using feature extraction. Then the values are matched in proximity of the coded values. Then the region of interest is calculated using the concept of convexity and background subtraction. The convex defect helps to define the contour efficiently. This method is invariant for different positions or direction of the gesture. It is able to detect the number of fingers individually and efficiently

Fusion of Image Contour Moments and Fourier Descriptors for the Hand Gesture Recognition

2012 ◽  
Vol 433-440 ◽  
pp. 5188-5192
Author(s):  
Hai Long Lei ◽  
Sheng Yang
Keyword(s):  
Gesture Recognition ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Fourier Descriptor ◽  
Bp Network ◽  
Moment Invariant ◽  
Hand Shape ◽  
Image Contour

Hand is a highly variable organ and hand features are easily affected by environmental factors. Considering the characteristics of hand gesture, a novel hand gesture recognition algorithm based on hybrid moments is presented. First, According to the color cue, the hand shape is available to extract from the complicated background, then the contour moment invariant and Fourier Descriptor are extracted and fused into a hybrid feature, finally the hybrid feature are put into the BP network to identity. The experimental results show that the method has better robustness and higher recognition rate.

Hand Gesture Recognition Algorithm: A Real-Time Human-Body-Based Approach

2013 ◽  
Vol 303-306 ◽  
pp. 1338-1343
Author(s):  
Xin Xiong Li ◽  
Yi Xiong ◽  
Zhi Yong Pang ◽  
Di Hu Chen
Keyword(s):  
Real Time ◽  
Gesture Recognition ◽  
Human Body ◽  
Skin Color ◽  
Average Rate ◽  
Vital Role ◽  
Recognition Algorithm ◽  
Hand Gesture Recognition ◽  
High Tech ◽  
Hand Gesture

Despite the appearance of high-tech human computer interface (HCI) devices, pattern recognition and gesture recognition with single camera are still playing vital role in research. A real-time human-body based algorithm for hand gesture recognition is proposed in this paper. The basis of our approach is a combination of moving object segmentation process and skin color detector based on human body structure to obtain the moving hands from input images, which is able to deal with the problem of complex background and random noises, and a rotate correction process for better finger detection. With ten fingers detected, more than 1000 gestures can be recognized before concerning motion paths. This paper includes experimental results of five gestures, which can be extended to other conditions. Experiments show that the algorithm can achieve a 99 percent recognition average rate and is suitable for real-time applications.

A Real Time Hand Gesture Recognition System Based on DFT and SVM

2013 ◽  
Vol 284-287 ◽  
pp. 3004-3009 ◽  
Author(s):  
Wen Her Chen ◽  
Ching Tang Hsieh ◽  
Tsun Te Liu
Keyword(s):  
Gesture Recognition ◽  
Skin Color ◽  
Recognition System ◽  
Extraction Process ◽  
Recognition Algorithm ◽  
Hand Gesture Recognition ◽  
Hand Gesture ◽  
Fast Detection ◽  
Starting Point ◽  
Boundary Deformation

Vision based band gesture recognition provides a more nature and powerful means for human-computer interaction. A fast detection process of hand gesture and an effective feature extraction process are presented. The proposed a hand gesture recognition algorithm comprises four main steps. First use Cam-shift algorithm to track skin color after closing process. Second, in order to extract feature, we use BEA to extract the boundary of the hand. Third, the benefits of Fourier descriptor are invariance to the starting point of the boundary, deformation, and rotation, and therefore transform the starting point of the boundary by Fourier transformation. Finally, outline feature for the nonlinear non-separable type of data was classified by using SVM. Experimental results showed the accuracy is 93.4% in average and demonstrated the feasibility of proposed system.

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