標題: NEURAL NETWORKS FOR PRECISE MEASUREMENT IN COMPUTER VISION SYSTEMS
作者: SU, CT
CHANG, CA
TIEN, FC
工業工程與管理學系
Department of Industrial Engineering and Management
關鍵字: PRECISE MEASUREMENT;DIMENSIONAL INSPECTION;COORDINATE CALIBRATION;ERROR CORRECTION;MEASUREMENT CORRECTION;NEURAL NETWORKS;BACK PROPAGATION;COMPUTER VISION
公開日期: 1-十一月-1995
摘要: Although computer vision systems have been successfully applied to some inspection tasks, they were generally not considered as precise measurement tools due to dimensional distortion and errors. This paper presents procedures to correct these errors for precise measurement. The first step is to formulate calibration models for image coordinate systems using neural networks. Then neural networks to model dimensional errors from the initial measurement are structured in a learning stage using standard parts. Finally these models are used to correct measurement errors in measurement tasks. These proposed procedures are implemented as an example.
URI: http://hdl.handle.net/11536/1672
ISSN: 0166-3615
期刊: COMPUTERS IN INDUSTRY
Volume: 27
Issue: 3
起始頁: 225
結束頁: 236
顯示於類別:期刊論文


文件中的檔案:

  1. A1995TJ91700002.pdf