Development of Enhanced Image Processing Algorithms for Precision Laser Cutting in Textile Automation

This paper presents the development of a prototype intelligent fabric cutting system that integrates laser technology with image processing for textile automation. Traditional fabric cutting methods are often inefficient, prone to error, and reliant on skilled manual labor. To address these challenges, the proposed system combines Computer-Aided Design (CAD), Computer-Aided Manufacturing (CAM), and computer vision techniques to detect and segment fabric patterns. These are then transformed into laser-compatible toolpaths for automated execution. Initial tests suggest the system is capable of detecting contour edges and translating them into precise cutting trajectories, with promising material efficiency. While full performance benchmarking remains ongoing, this work contributes a foundational step toward scalable, intelligent textile cutting systems..

Authors

Institutions

Publication Details

Published
2025-08-27
DOI
https://doi.org/10.1109/inecce64959.2025.11150844
Primary Topic
Laser Material Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of Enhanced Image Processing Algorithms for Precision Laser Cutting in Textile Automation

Abdul Nasir Abd. Ghaffar, Muhamad Ridzuan Radin Muhamad Amin, Danial Nuqman Khairul Nizam
Laser Material Processing Techniques
article

Development of Enhanced Image Processing Algorithms for Precision Laser Cutting in Textile Automation

Abdul Nasir Abd. Ghaffar, Muhamad Ridzuan Radin Muhamad Amin, Danial Nuqman Khairul Nizam
article en

Abstract

This paper presents the development of a prototype intelligent fabric cutting system that integrates laser technology with image processing for textile automation. Traditional fabric cutting methods are often inefficient, prone to error, and reliant on skilled manual labor. To address these challenges, the proposed system combines Computer-Aided Design (CAD), Computer-Aided Manufacturing (CAM), and computer vision techniques to detect and segment fabric patterns. These are then transformed into laser-compatible toolpaths for automated execution. Initial tests suggest the system is capable of detecting contour edges and translating them into precise cutting trajectories, with promising material efficiency. While full performance benchmarking remains ongoing, this work contributes a foundational step toward scalable, intelligent textile cutting systems..

Universiti Malaysia Pahang Al-Sultan Abdullah (MY)
Openalex Percentile: Top 74%
Laser Material Processing Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Development of Enhanced Image Processing Algorithms for Precision Laser Cutting in Textile Automation — Abdul Nasir Abd. Ghaffar, Muhamad Ridzuan Radin Muhamad Amin, et al. · (2025) | TGRS Research Map | TGRS