Hand Gesture Recognition for MP3 Player using Image Processing Technique and PIC16F8779
Devikarani Patil1, Varalakshmi B.D2
1Devikarani Patil, PG Student, Department of Computer Science and Engineering, Acharya Institute of Technology, Bangalore, India.
2Varalakshmi B. D, Assoc. Prof., Department of Computer Science and Engineering, Acharya Institute of Technology, Bangalore, India.
Manuscript received on November 02, 2014. | Revised Manuscript received on November 04, 2014. | Manuscript published on November 05, 2014. | PP: 45-49 | Volume-4 Issue-5, November 2014. | Retrieval Number: D2352094414/2014©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The scope of the project is to control MP3 player using gesture. Here, gesture image is taken from Web camera and image will be processed in remote interface using MATLAB controller. But, the challenging problem is that capturing the image from external device does not depend on unique only and Identification of the exact action from an unclear image is not an easy task. Hence, capturing action from the images is always puzzling task of separating different sources of images when its different or noisy. Finally, the images are forwarded to MATLAB to compare the images with our knowledge database via three dimension (x, y, and z) readings of a particular object. So if we move any object in any direction then the corresponding values are noted by the accelerometer. Most of the music players are controlled through the remote controls which contain buttons. But through embedding the PIC16F8779 controller, we can make music player be controlled by gesture performance in the air. The application of this three axis controller together with suitable interfacing with the PIC16F8779 micro controller and the music player development through coding in software platform such as MPLab IDE which could recognize the terminal input instructions and perform functions like play, stop, play back and play forward of music player controlled by gesture. We need to move the accelerometer in a particular set of directions then it will recognize one of the directions like REWIND, FORWARD, PLAY and STOP and operate the songs present in the list of music system. Additionally, Karhunen-Loeve (K-L) Transform is used to capture the image without any noise and accurate in result and Canny Edge Detection for image segmentation and edge detection using Principal component analysis (PCA) which add more value in expected result.
Keywords: Hand Gesture Recognition, Karhunen-Loeve (KL) Transform, Skin Filtering, Canny Edge Detection, Image Segmentation, Human Computer Interaction, matching algorithm; PIC16F8779