Image Object Replacement Algorithm Applied to Mobile Devices

• Main Authors: Wei-Syuan Wang, 王偉諠
• Other Authors: Jen-Chang Liu
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/20543036036980308801

碩士 === 國立暨南國際大學 === 資訊工程學系 === 99 === The applications of mobile devices have been rapidly developed on smart phones and tablets in recent years. Along with the rapid growth of the Internet community over the past decade, Mobile Computing has become a part of our everyday lives. Most mobile devices have built-in cameras. Therefore, the image processing applications on mobile devices are receiving more attentions, such as photo editing, image inpainting, and special effects on images. The difficulties of developing image processing algorithms on mobile devices are due to the limited resources and processing speed on these embedded systems. In this thesis, we propose an image object replacement algorithm on mobile devices. First, the user can take a photograph. On the touch screen, he/she can draw the contour around the object for replacement. The system will display the photograph on the camera view, where the region inside the contour will be transparent. Secondly, the user can take a photograph again by aligning the transparent region with the target object in the real world. After taking the second image, he/she can draw the contour around the target object. The application will replace the target object of the second image on the background of the first image to compose a synthesized image. The digital image processing technologies applied include contour extraction, image inpainting, and color transfer. Contour extraction is used to modify the drawn object contour by the user. Image inpainting is used to fix the gaps between the target object and the background. We use color transfer to transfer the color tone of the target object from the replacement object. The experimental results on the contour extraction, image inpainting, and color transfer are presented. Enormous examples are examined to show the effects of the proposed image object replacement algorithm. Our image inpainting algorithm is implemented on mobile devices, and the execute time on the mobile devices is studied.