Enhancement of depth value approximation using noise filtering and inverse perspective mapping techniques for image based modelling / Rahmita Wirza O.K Rahmat, Ng Seng Beng and Intan Syaherra Ramli

This article proposes the methods to enhance the depth value approximation in 3D Image Based Modelling for complex object. Fundamentally, the fast and accurate depth value approximation is crucial as the 3D modelling used in virtual and augmented reality applications, reverse engineering, and the ar...

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Main Authors: O.K Rahmat, Rahmita Wirza, Ng, Seng Beng, Ramli, Intan Syaherra
Format: Article
Language:English
Published: UiTM Cawangan Perlis 2023
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/87243/1/87243.pdf
https://ir.uitm.edu.my/id/eprint/87243/
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spelling my.uitm.ir.872432023-11-16T03:50:06Z https://ir.uitm.edu.my/id/eprint/87243/ Enhancement of depth value approximation using noise filtering and inverse perspective mapping techniques for image based modelling / Rahmita Wirza O.K Rahmat, Ng Seng Beng and Intan Syaherra Ramli jcrinn O.K Rahmat, Rahmita Wirza Ng, Seng Beng Ramli, Intan Syaherra System design This article proposes the methods to enhance the depth value approximation in 3D Image Based Modelling for complex object. Fundamentally, the fast and accurate depth value approximation is crucial as the 3D modelling used in virtual and augmented reality applications, reverse engineering, and the architecture. Therefore, the enhanced method must be robust against the challenges with noise, complexity, distortion and longer processing time. In this experiment, five small and complex objects were captured using a turntable, laptop, and a webcam. The feature points between images were tracked and matched using good features to tracks and Pyramidal Lucas Kanade's optical flow. Next, the depth value was approximated using trigonometry equation. To enhance the accuracy, the noise filtering, and Inverse Perspective Mapping (IPM) were introduced. The results show that the average error based on the approximated width and depth dimensions was 3.27% and 6.88% compared with the actual object. Furthermore, the processing speed was 1519 points per second. Therefore, this method enhanced the depth value approximation, which can be used to build the full texture 3D model in future. UiTM Cawangan Perlis 2023 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/87243/1/87243.pdf Enhancement of depth value approximation using noise filtering and inverse perspective mapping techniques for image based modelling / Rahmita Wirza O.K Rahmat, Ng Seng Beng and Intan Syaherra Ramli. (2023) Journal of Computing Research and Innovation (JCRINN) <https://ir.uitm.edu.my/view/publication/Journal_of_Computing_Research_and_Innovation_=28JCRINN=29/>, 8 (2): 24. pp. 246-264. ISSN 2600-8793
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic System design
spellingShingle System design
O.K Rahmat, Rahmita Wirza
Ng, Seng Beng
Ramli, Intan Syaherra
Enhancement of depth value approximation using noise filtering and inverse perspective mapping techniques for image based modelling / Rahmita Wirza O.K Rahmat, Ng Seng Beng and Intan Syaherra Ramli
description This article proposes the methods to enhance the depth value approximation in 3D Image Based Modelling for complex object. Fundamentally, the fast and accurate depth value approximation is crucial as the 3D modelling used in virtual and augmented reality applications, reverse engineering, and the architecture. Therefore, the enhanced method must be robust against the challenges with noise, complexity, distortion and longer processing time. In this experiment, five small and complex objects were captured using a turntable, laptop, and a webcam. The feature points between images were tracked and matched using good features to tracks and Pyramidal Lucas Kanade's optical flow. Next, the depth value was approximated using trigonometry equation. To enhance the accuracy, the noise filtering, and Inverse Perspective Mapping (IPM) were introduced. The results show that the average error based on the approximated width and depth dimensions was 3.27% and 6.88% compared with the actual object. Furthermore, the processing speed was 1519 points per second. Therefore, this method enhanced the depth value approximation, which can be used to build the full texture 3D model in future.
format Article
author O.K Rahmat, Rahmita Wirza
Ng, Seng Beng
Ramli, Intan Syaherra
author_facet O.K Rahmat, Rahmita Wirza
Ng, Seng Beng
Ramli, Intan Syaherra
author_sort O.K Rahmat, Rahmita Wirza
title Enhancement of depth value approximation using noise filtering and inverse perspective mapping techniques for image based modelling / Rahmita Wirza O.K Rahmat, Ng Seng Beng and Intan Syaherra Ramli
title_short Enhancement of depth value approximation using noise filtering and inverse perspective mapping techniques for image based modelling / Rahmita Wirza O.K Rahmat, Ng Seng Beng and Intan Syaherra Ramli
title_full Enhancement of depth value approximation using noise filtering and inverse perspective mapping techniques for image based modelling / Rahmita Wirza O.K Rahmat, Ng Seng Beng and Intan Syaherra Ramli
title_fullStr Enhancement of depth value approximation using noise filtering and inverse perspective mapping techniques for image based modelling / Rahmita Wirza O.K Rahmat, Ng Seng Beng and Intan Syaherra Ramli
title_full_unstemmed Enhancement of depth value approximation using noise filtering and inverse perspective mapping techniques for image based modelling / Rahmita Wirza O.K Rahmat, Ng Seng Beng and Intan Syaherra Ramli
title_sort enhancement of depth value approximation using noise filtering and inverse perspective mapping techniques for image based modelling / rahmita wirza o.k rahmat, ng seng beng and intan syaherra ramli
publisher UiTM Cawangan Perlis
publishDate 2023
url https://ir.uitm.edu.my/id/eprint/87243/1/87243.pdf
https://ir.uitm.edu.my/id/eprint/87243/
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score 13.211869