An automatic template generating method of machine vision system in TFT LCD assembly and positioning process with genetic algorithm

Purpose - The purpose of this paper is to propose an automatic pattern matching template generating method for the automatic optical inspection system in TFT LCD assembly and positioning process, to improve the conventional image technology. Besides, focusing on integrating the image system with the...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Assembly automation 2009-01, Vol.29 (1), p.41-48
Hauptverfasser: Lin, Chern-Sheng, Wu, Kuo-Chun, Lay, Yun-Long, Lin, Chi-Chin, Lin, Jim-Min
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Purpose - The purpose of this paper is to propose an automatic pattern matching template generating method for the automatic optical inspection system in TFT LCD assembly and positioning process, to improve the conventional image technology. Besides, focusing on integrating the image system with the existing control system, the double aligner mark searching time is decreased to reduce the working time of the integrated system.Design methodology approach - The improved pattern matching method of genetic algorithm was adopted, including setting for template image selecting, encoding, calculating fitness function, pattern matching, template generating and genetic algorithm steps. The predetermined pixels were selected from the target template based on the minimum difference to the block image to be tested by utilizing the genetic algorithm, and the other pixels which have not been selected were neglected.Findings - The selected pixels were encoded for recording by sequence mode, and then the target template and the image to be tested were compared based on the calculated fitness function. This method has the advantages of using the fitness function to reduce the searching time, with the help of genetic algorithm to find the optimal target template, and saving memory space by recording target template based on the sequence mode.Research limitations implications - The genetic algorithm used in this study is a kind of optimal tool free from gradient data. As long as the fitness function and after continuous iteration are determined, the optimal solution can be found out, and then the optimal target template can be generated.Practical implications - This system uses fitness function to reduce the pattern matching time. Plural pixels are preset inside the target template, and its fitness function value is calculated. When the target template is compared with the image to be tested, only the fitness function value (also the difference of the plural pixels) is calculated and compared.Originality value - The remaining pixels are neglected, so that the searching time can be reduced greatly. The sequence mode is used to save the required memory space for recording target template. Since sequence mode is adopted to record the information of selected pixels, lots of required memory space for recording target template information will be saved.
ISSN:0144-5154
2754-6969
1758-4078
2754-6977
DOI:10.1108/01445150910929848