Comparison Of Processing Time Of Different Size Of Images And Video Resolutions For Object Detection Using Fuzzy Inference System

Object Detection with small computation cost and processing time is a necessity in diverse domains such as traffic analysis security cameras video surveillance etc .With current advances in technology and decrease in prices of image sensors and video cameras the resolution of captured images is more than 1MP and has higher frame rates. This implies a considerable data size that needs to be processed in a very short period of time when real-time operations and data processing is needed. Real time video processing with high performance can be achieved with GPU technology. The aim of this study is to evaluate the influence of different image and video resolutions on the processing time number of objects detections and accuracy of the detected object. MOG2 algorithm is used for processing video input data with GPU module. Fuzzy interference system is used to evaluate the accuracy of number of detected object and to show the difference between CPU and GPU computing methods.