This paper is published in Volume-4, Issue-3, 2018
Area
Computer Vision
Author
Ravi Satvik Gorthi
Co-authors
Bhargava Krishna Pasupuleti, Datharla Pandu Ranga Rohith, R. Sathya
Org/Univ
SRM University, Chennai, Tamil Nadu, India
Pub. Date
03 May, 2018
Paper ID
V4I3-1213
Publisher
Keywords
Image processing, Image compression, Image classification, Feature matching

Citationsacebook

IEEE
Ravi Satvik Gorthi, Bhargava Krishna Pasupuleti, Datharla Pandu Ranga Rohith, R. Sathya. Object recognition using surveillance dynamic background for cluster recognition, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Ravi Satvik Gorthi, Bhargava Krishna Pasupuleti, Datharla Pandu Ranga Rohith, R. Sathya (2018). Object recognition using surveillance dynamic background for cluster recognition. International Journal of Advance Research, Ideas and Innovations in Technology, 4(3) www.IJARIIT.com.

MLA
Ravi Satvik Gorthi, Bhargava Krishna Pasupuleti, Datharla Pandu Ranga Rohith, R. Sathya. "Object recognition using surveillance dynamic background for cluster recognition." International Journal of Advance Research, Ideas and Innovations in Technology 4.3 (2018). www.IJARIIT.com.

Abstract

The paper aims to develop an object detection method combining classification and cluster. Object detection is a challenging, yet important vision task. It is a critical part in many applications such as image search, image auto-annotation and scene understanding. Our proposed method work is dividing in two part.1) image classification and 2) clustering method. In this classification part LTP (local ternary pattern) features used to match the dataset image. This LTB features extracted from our input de-blurred image. Finally object is classified and then object is detected using clustering methods. As far as the robustness and effectiveness are concerned, our method is better than the existing image segmentation algorithms.