Implementation of mobile platform using Qt and OpenCV for image processing applications

The new advancement in technology made mobile phone as smart phone with highly computing capabilities and low processing power. Currently, achieving real-time image processing routines such as convolution, thresholding, edge detection and some of the complex media applications is a challenging tasks embedded in smart phone, because of limited memory. An open software framework, Symbian OS is used in mobile devices to provide a good starting point for developing the multitasking kernel, integrated with communication protocols, data management and graphical user interface for reducing the total development time. To resolve the problems faced by the image processing applications in mobile phones a new application environment was developed. This environment provides the resources available in the operating system which runs on the hardware with complex image processing libraries. This paper presents the capture of an image from the printed media, applied to image processing algorithms to scaling and translation of the image, wipe out the noise, and detect the edges. Then the developed software chops the comics strip along border into individual units, store on the permanent memory and and display on the handset. The application Graphical User Interface was designed using Qt and Visual C++ Integrated Development Environment (IDE) for implementing image processing algorithm using Open Source Computer Vision Library (OpenCv). Many image processing methods pre-processes images, which are Set Region of Interest (ROI) crop, flattening with Gaussian Filter, RGB to Grey scale adaptation, Histogram equalization and Detect Border. This developed software integrated in mobiles by the cross compilation of Qt and the OpenCV software for windows XP Operating system. The result utilized the CANNY method in finding edges of the image using OpenCV. The integrated approach succeeded in mobile phone by detecting the edges, chopping the images to required format of individual units, then stored it using OpenCV and finally displayed on a mobile phone without any loss of image information. The impacts of memory latency, synchronization and the data management overhead are in significant manner.