TELKOMNIKA Telecommunication Computing Electronics and Control
Stereo matching algorithm using census transform and segment tree for depth estimation

TELKOMNIKA Telecommunication Computing Electronics and Control
Stereo matching algorithm using census transform and segment tree for depth estimation

Census transform
Cyber-physical system
Segment-tree cost aggregation
Stereo matching algorithm
Stereo vision
Weighted median filtering

This article proposes an algorithm for stereo matching corresponding
process that will be used in many applications such as augmented reality,
autonomous vehicle navigation and surface reconstruction. Basically,
the proposed framework in this article is developed through a series of
functions. The final result from this framework is disparity map which this
map has the information of depth estimation. Fundamentally, the framework
input is the stereo image which represents left and right images respectively.
The proposed algorithm in this article has four steps in total, which starts
with the matching cost computation using census transform, cost aggregation
utilizes segment-tree, optimization using winner-takes-all (WTA) strategy,
and post-processing stage uses weighted median filter. Based on the
experimental results from the standard benchmarking evaluation system
from the Middlebury, the disparity map results produce an average low noise
error at 9.68% for nonocc error and 18.9% for all error attributes.
On average, it performs far better and very competitive with other available
methods from the benchmark system.

Muhammad Nazmi Zainal Azali, Rostam Affendi Hamzah, Zarina Mohd Noh, Izwan Zainal Abidin, Tg Mohd Faisal Tengku Wook

http://telkomnika.uad.ac.id

Nov 14, 2022

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