It is required to study images by using computer vision for modern intelligent applications. But it is often found that it is very difficult to apply computer vision on daily appliances as computer vision requires high processing power and consumes heavy hardware when under use. Thus it becomes difficult for a normal system to work on the schematics of computer vision for processing the environment. Hence the authors propose a novel model of image segmentation and classification by using the principles of operating systems and parallel processing to speed up the current image segmentation algorithms and reduce the current CPU usage.