Real Time Video Processing and Object Detection on Mobile

As Smartphone is getting more potent, can do more superior stuffs that previous required a computer. For employing the high processing power of Smartphone is mobile computer vision, the ability for a device to capture; process; analyze; under- standing of images. For mobile computer vision, Smartphone must be faster and real time. In this book three applications have been developed on an Android platform using OpenCV and in built core library with own implemented algorithms called as CamTest. Real Time video processing methods are applied to each video frame captured from Smartphone, that is running on an Android platform. Effi- ciency of two Android applications have been compared with respect to video frame processing rate and found that OpenCV performs faster than the CamTest. Real Time object detection in mobile computer vision on Android is complicated task as it requires high performance. We analyzed object detection algorithms such as Scale Invariant Feature Transform (SIFT), Speeded Up Feature Transform (SURF), Fea- tures from Accelerated Segment Test (FAST), Maximally Stable Extremal Regions (MSER), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent.

Autorentext

Prof. Dr. Pramod J. Deore, BE (Electronics), ME ( Instrumentation), Phd (E & Tc). Prof. Shailaja Arjun Patil, BE (Electronics), ME (Electronics), Phd (Persuing), Mr.Chaudhari Sunil Bhimsing, BE (Electronics), ME ( E & Tc)E & Tc department, R C Patel Institute of Technology, Shirpur, Dist: Dhule, Maharashtra, India.