完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Perng, Der-Baau | en_US |
dc.contributor.author | Liu, Hsiao-Wei | en_US |
dc.contributor.author | Chang, Ching-Ching | en_US |
dc.date.accessioned | 2014-12-08T15:20:32Z | - |
dc.date.available | 2014-12-08T15:20:32Z | - |
dc.date.issued | 2011-12-01 | en_US |
dc.identifier.issn | 0268-3768 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1007/s00170-011-3338-y | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/14625 | - |
dc.description.abstract | Light-emitting diodes (LED) are used in many different applications. However, some LED defects are unavoidable in large-volume fabrication and taping processes. These defects may include missing components, incorrect orientations, inverse polarity, mouse bites, missing gold wires, and surface stains. Human visual inspection has traditionally been used in LED-packaging factories. However, it is subjective, time consuming, and lacking consistent inspection results. This paper proposes a machine vision system combining an automatic system-generated inspection regions (IR) method to inspect two types of LED surface-mounted devices (SMDs). Experimentation revealed that the proposed automatic inspection method could successfully detect defects with up to 95% accuracy for both types (Types 1 and 2) of SMD LEDs. The online inspecting speed was on average under 0.3 s per image. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | LED | en_US |
dc.subject | Vision inspection | en_US |
dc.subject | Machine vision | en_US |
dc.subject | Defect detection | en_US |
dc.title | Automated SMD LED inspection using machine vision | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1007/s00170-011-3338-y | en_US |
dc.identifier.journal | INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | en_US |
dc.citation.volume | 57 | en_US |
dc.citation.issue | 9-12 | en_US |
dc.citation.spage | 1065 | en_US |
dc.citation.epage | 1077 | en_US |
dc.contributor.department | 工業工程與管理學系 | zh_TW |
dc.contributor.department | Department of Industrial Engineering and Management | en_US |
dc.identifier.wosnumber | WOS:000296629100019 | - |
dc.citation.woscount | 9 | - |
顯示於類別: | 期刊論文 |