Faster Image Segmentation and Classification Using Machine Learning and Parallel Processing

Volume 11 Issue 4 April - June 2017

Research Paper

Faster Image Segmentation and Classification Using Machine Learning and Parallel Processing

Shaik Naseera*, Pranjal Srivastava**, Apoorv Gupta***, Swarna Lakshmi****, Mahak Gupta*****

* Associate Professor, School of Computer Science and Engineering, VIT University, Vellore, India.

**-***** Scholar, School of Computer Science and Engineering, VIT University, Vellore, India.

Naseera, S., Srivastava, P., Gupta, L., Lexshmi, S., and Gupta, M. (2017). Faster Image Segmentation and Classification Using Machine Learning and Parallel Processing. i-manager’s Journal on Software Engineering, 11(4), 18-23. https://doi.org/10.26634/jse.11.4.13817

Abstract

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.