The high‐speed measurement of a partial area imaging system applied to photoresist development processing

Lin, Chern‐Sheng; Lay, Yun-Long; Chan, Shi‐Xiang; Ho, Chien-Wa; Chiou, Yih-Chih

doi:10.1080/02533839.2005.9671039

Cited by 2 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This research combines digital image processing and electrical tests to send signals to a thin film transistor (TFT) liquid crystal display (LCD) by a signal generator, and then gets an image by a video camera and looks for defects during digital image processing (Lin et al, 2006(Lin et al, , 2005(Lin et al, , 2003. Figure 1 shows the machinery layout and the operationrelated equipment including monitor, keyboard, mouse, and start and stop buttons.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

High‐speed TFT LCD defect‐detection system with genetic algorithm

Lin

Liao

Lay

et al. 2008

Assembly Automation

Self Cite

View full text Add to dashboard Cite

Purpose-The purpose of this research is to develop an automatic optical inspection system for thin film transistor (TFT) liquid crystal display (LCD). Design/methodology/approach-A new algorithm that accounts for the closing, opening, etching, dilating, and genetic method is used. It helps to calculate the location and rotation angle for transistor patterns precisely and quickly. The system can adjust inspection platform parameters according to viewed performance. The parameter adaptation occurs in parallel with running the genetic algorithm and imaging processing methods. The proposed method is compared with the algorithms that use artificial parameter sets. Findings-This system ensures high quality in an LCD production line. This multipurpose image-based measurement method uses unsophisticated and economical equipment, and it also detects defects in the micro-fabrication process. Originality/value-The experiment's results show that the proposed method offers advantages over other competing methods.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%