Adaptive multi-focus regions defining and implementation on mobile phone

Multi–focus application is not an unknown new thread in image processing. At the present, there are have many methods and solutions to solve this problem, but each solution has its own advantages and disadvantages. In addition, in recent times, the rapid development of mobile multi-focus processing has been a trend for new technology development, so multi-focus processing is being improved efficiency and quality. This thesis proposes an object based multi-focus method which is implemented on mobile device. To achieve low computation complexity in the same object determination for multi input image, this thesis adapts Oriented FAST and Rotated BRIEF algorithm to detect feature points. The most important is the precise detection of the regions through Edge and Contour detection. Then apply the Fusion algorithm to process the region recognition results. To perform the identification of focused regions and the objects within the image, this thesis proposes the method of aggregating information from the recognition of the edge on image. In this thesis, we will focus on building edge and contour detection based on Adaptive Threshold. This method, the maximum efficiency compared to the method through Global Threshold. Plus, that's the information of the image through partitioning and incorporating algorithms in the image processing to determine the focus areas of the image. By all algorithms and implementing methods, we will carry out entirely on mobile platform. We intend to take advantage of smartphone’s enhanced flexibility and high performance to make the selection of areas via the touch screen of the mobile device.