@inproceedings{f471fb472555425f90481dcc25763049,
title = "Edge reconstruction of LED probes using various segmentation and the averaging of sub-pixels",
abstract = "LED probes are essential for testing the quality of LEDs, gaining its attention among industrial applications. Disturbance factors such as dust or noise affections may occur during the manufacturing process of the LED probes, which leads angle error to increase. With the increasing demand for LED probes, higher precision and efficiency are expected by users. Efficient method for edge detection and the preciseness of angle is crucial in our study. The previous study presents a method using Scharr Edge Detection and Adaptive Reconstruction. In this paper, we add a new method based on various segmentation and the averaging of sub-pixels(VSAS). Experimental result indicates that this method provides higher precision, with and an average error less than 1 % compared to the other previous methods.",
keywords = "Edge detection, LED, VSAS method, probe, sub-pixels",
author = "Liu, {Ying Hao} and Su, {Chung Yen} and Yu, {Li An} and Chen, {Nai Kuei}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; International Conference on Intelligent Informatics and Biomedical Sciences, ICIIBMS 2015 ; Conference date: 28-11-2015 Through 30-11-2015",
year = "2016",
month = mar,
day = "22",
doi = "10.1109/ICIIBMS.2015.7439459",
language = "English",
series = "ICIIBMS 2015 - International Conference on Intelligent Informatics and Biomedical Sciences",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5--8",
booktitle = "ICIIBMS 2015 - International Conference on Intelligent Informatics and Biomedical Sciences",
}