Publication Type:

Conference Paper

Source:

2017 4th International Conference on Advanced Computing and Communication Systems, ICACCS 2017, Institute of Electrical and Electronics Engineers Inc. (2017)

ISBN:

9781509045594

URL:

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030213680&doi=10.1109%2fICACCS.2017.8014572&partnerID=40&md5=399ad62274c29a54c31a38d24a289e20

Keywords:

Color, Color images, Color objects, Computer vision, Edge detection, Feature detection, Feature extraction, Harris corner detection, Object Detection, Object recognition, Research problems, Scene-based, SIFT, SURF

Abstract:

The object recognition and classification is a research problem in the field of computer vision. The computers are trained to automatically identify various objects present in a scene based on various features extracted from it. These features should be the unique ones that will differentiate one object from the other. In this paper, SURF features are extracted from the color image and combined to detect a color object. Based on the experimental results we derive an efficient way to detect the SURF features. © 2017 IEEE.

Notes:

cited By 0; Conference of 4th International Conference on Advanced Computing and Communication Systems, ICACCS 2017 ; Conference Date: 6 January 2017 Through 7 January 2017; Conference Code:130103

Cite this Research Publication

M. Muthugnanambika and Padmavathi, S., “Feature detection for color images using SURF”, in 2017 4th International Conference on Advanced Computing and Communication Systems, ICACCS 2017, 2017.

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