Stereo Matching Based On Absolute Differences For Multiple Objects Detection

Hamzah, Rostam Affendi and Gan, Melvin Yeou Wei and Nik Anwar, Nik Syahrim (2019) Stereo Matching Based On Absolute Differences For Multiple Objects Detection. TELKOMNIKA (Telecommunication Computing Electronics And Control), 17 (1). pp. 261-267. ISSN 1693-6930

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Abstract

This article presents a new algorithm for object detection using stereo camera system. The problem to get an accurate object detection using stereo camera is the imprecise of matching process between two scenes with the same viewpoint. Hence, this article aims to reduce the incorrect matching pixel with four stages. This new algorithm is the combination of continuous process of matching cost computation, aggregation, optimization and filtering. The first stage is matching cost computation to acquire preliminary result using an absolute differences method. Then the second stage known as aggregation step uses a guided filter with fixed window support size. After that, the optimization stage uses winner-takes-all (WTA) approach which selects the smallest matching differences value and normalized it to the disparity level. The last stage in the framework uses a bilateral filter. It is effectively further decrease the error on the disparity map which contains information of object detection and locations. The proposed work produces low errors (i.e., 12.11% and 14.01% nonocc and all errors) based on the KITTI dataset and capable to perform much better compared with before the proposed framework and competitive with some newly available methods.

Item Type:	Article
Subjects:	T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Faculty of Electrical and Electronic Engineering Technology > Department of Electronic and Computer Engineering Technology
Depositing User:	Mohd Hannif Jamaludin
Date Deposited:	05 Mar 2020 12:12
Last Modified:	05 Mar 2020 12:12
URI:	http://eprints.utem.edu.my/id/eprint/24038
Statistic Details:	View Download Statistic

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