Highly optimized OpenCV based cell phone

The new advancement in technology made cell phone as a smart phone with highly computing capabilities and low processing power. Currently, achieving real-time image processing routines such as convolution, edge detection, thresholding and some of complex media applications is a challenging task with the smart phone, because of limited memory and power constraints. An open software framework, Symbian OS is used in cell 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 image processing applications in cell phones, new application environment is developed. This environment provides the resources available in the operating system which runs on the hardware with complex image processing libraries. These papers presents the capturing of an image from the printed media, applies to image processing algorithms to scaling and translation of the image, wipe out the noise, background subtraction, image rotation and detect edges. The developed software chops the comics strip along border into individual units, store on the permanent memory and and display on the handset. Implementation of image processing algorithm using Open Source Computer Vision Library (OpenCv), with Visual C++ Integrated Development Environment (IDE) and application Graphical User Interface is designed using Qt. Images are pre-processed with several image processing techniques, such as, RGB to Grey scale conversion, smoothening using Gaussian Filter, Histogram equalization, Detect Border (cumulative sum) and Set Region of Interest (ROI) crop. This developed software integrated in cells by the cross compilation of Qt and the OpenCV software for an Operating system. The result utilized the CANNY method in finding edges of the image using OpenCV. The integrated approach succeeded in cell phone by detecting the edges, chopp- - ing the images to required format of individual units, then stored it using OpenCV and finally displayed on a cell phone without any loss of image information. The impacts of memory latency, synchronization and the data management overhead are also studied and presented in this paper.