Simple MATLAB Gesture Recognition with Code Implementation

Application Background: In today's society, with continuous technological development, gesture recognition technology has become increasingly prevalent and is widely applied in various fields such as smart homes and virtual reality. This article introduces a MATLAB-based simple gesture recognition code that is executable and suitable for beginners' learning purposes. Gesture Recognition: The program contains three predefined gesture images (rock, paper, scissors) that are matched against gestures captured through camera input for identification. The code implementation involves comparing real-time camera frames with stored template images using similarity metrics. Gesture recognition has broad application prospects, such as controlling home appliances in smart home systems through hand gestures. Key Technologies: The program utilizes digital image processing techniques including image segmentation, edge detection, and template matching. For image segmentation, the code implements threshold-based segmentation methods that effectively separate different objects in images using functions like graythresh() and imbinarize(). In edge detection, the Canny operator is employed through MATLAB's edge() function with 'Canny' parameter, ensuring accurate edge detection with optimized noise reduction. For template matching, the program uses gray-level co-occurrence matrix (GLCM) approach implemented via graycomatrix() and graycoprops() functions, enabling efficient and accurate pattern matching through statistical texture analysis. In summary, this program helps beginners quickly understand gesture recognition technologies and provides basic introductions to their practical applications. The code structure includes clear function divisions for image preprocessing, feature extraction, and classification comparison, making it an ideal starting point for learning computer vision concepts.