2021
DOI: 10.46338/ijetae0821_07
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mproved Stereo Matching Algorithm based on Census Transform and Dynamic Histogram Cost Computation

Abstract: Stereo matching is a significant subject in the stereo vision algorithm. Traditional taxonomy composition consists of several issues in the stereo correspondences process such as radiometric distortion, discontinuity, and low accuracy at the low texture regions. This new taxonomy improves the local method of stereo matching algorithm based on the dynamic cost computation for disparity map measurement. This method utilised modified dynamic cost computation in the matching cost stage. A modified Census Transform… Show more

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Cited by 3 publications
(2 citation statements)
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References 38 publications
(47 reference statements)
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“…Sometimes in circumstances, the reaction of the shock and/or vibration environment will play a significant part in the overall damage. These dynamic effects can cause the structure to resist substantial amplitudes and/or acceleration levels, whether generated by the environment, manufacture, shipping, handling, operation, or any other source [13,14]. As a result, the issue of shielding PCBs against the effects of acute vibration should be addressed.…”
Section: Parameter Indexmentioning
confidence: 99%
“…Sometimes in circumstances, the reaction of the shock and/or vibration environment will play a significant part in the overall damage. These dynamic effects can cause the structure to resist substantial amplitudes and/or acceleration levels, whether generated by the environment, manufacture, shipping, handling, operation, or any other source [13,14]. As a result, the issue of shielding PCBs against the effects of acute vibration should be addressed.…”
Section: Parameter Indexmentioning
confidence: 99%
“…Figure 1. The stages of the stereo vision framework [8] Local approaches utilise disparity based on the relationship between pixel intensities (grayscale, RGB colours, texture patterns) inside a certain local support window based on the connections between pixels in close proximity to one another in the corresponding image [12]. These methods are sometimes referred to as window-based or region-based approaches.…”
Section: Introductionmentioning
confidence: 99%