| Summary: | 碩士 === 國立成功大學 === 工程科學系碩博士班 === 101 === Abstract
Human vision is one of our most advanced senses; therefore, image for the human’s sense is very important. Along with the rapid improvement in the development of computer technology and execution speed, image processing techniques have also matured. However, in the past, positioning cameras have been used nearly exclusively for detecting and tracking moving objects. If the moving objects move outside the lens’ view area, it can not be tracked. In order to improve this weakness and reduce blind spots, this thesis proposes a real-time object tracking gesture recognition system.
The system architecture is composed as follows:
1. Using a camera to capture images.
2. Using USB2.0 to transmit the images to a computer.
3. Using the YCbCr color space model to analyze and separate skin color from the background.
4. Removing the image noises with a morphological algorithm.
5. Calculating coordinates via the marginalization of the moving objects and histogram statistics.
6. Via USB2.0, the computer can determine movement trajectories to drive the servo motor, which can effectively track objects.
7. According to the vector analysis of moving coordinates, moving direction of hands can be recognized. The different sets of moving direction of hands can be defined as many gestures. In order to make users understand the actions recognized by the system easily, this thesis explores six types of gestures.
8. In addition, this thesis additionally focuses on a moving object and sets a moving mask, which can reduce system operation time and advance functions.
This thesis invited ten participants, and through their cooperation it was verified that this system can detect and track moving objects and also recognize six types of gestures.
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