Download Computer Vision for Electronics Manufacturing by L. F. Pau (auth.) PDF

By L. F. Pau (auth.)

DEFECT percentage OF DETECTION preliminary fee DETECTION fee INSPECTOR three COMPLEXITY OF occasions PAN OF acting o~ ________________________ o~ ______________________ __ -;. INSPECTION activity -;. visible INSPECTION Fagure 1. traits in relatives among the complexity of inspection projects, illness detection charges (absolute and relative), and inspection time. without reference to the must haves defined above, and with the excep­ tion of particular known software platforms (e.g., bare-board PCB inspection, wafer inspection, solder joint inspection, linewidth degree­ ment), imaginative and prescient platforms are nonetheless now not chanced on usually in modern-day electronics factories. along with fee, a few significant purposes for this absence are: 1. The detection robustness or accuracy continues to be inadequate. 2. the complete inspection time is usually too excessive, even supposing this may often be attributed to mechanical dealing with or sensing. three. There are chronic gaps between approach engineers, CAD en­ gineers, production engineers, try experts, and machine imaginative and prescient experts, as difficulties dominate the daily interac­ tions and forestall the institution of belief. four. machine imaginative and prescient experts occasionally nonetheless think that their contributions are common, in order that version to every actual challenge turns into tedious, or stumbles over the inadequate availabIlity of multidisciplinary services. no matter if we love it or no longer, we needs to nonetheless use acceptable sensors, lights, and combina­ tions of algorithms for every classification of purposes; likewise, we can't layout mechanical dealing with, illumination, and sensing in isolation from every one other.

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The images of the corresponding logic states are subtracted (Algorithm Subtr-l). Image enhancement is carried out through table lookup (Algorithm LUT-l). Doing this for a number of subsequent logic states by image sequence analysis reveals the first occurrence of a failure and its subsequent spreading until the bond pads are reached. The logic state images can be synchronously subtracted from those of a reference device or from the logic state image of the same device in the previous logical state.

OBIC and EBIC Image Processing When a sequence of logical input stimuli are applied, two types of image processing take place, both preceded by thresholding (Algorithms Thresh-n), possibly filtering (Algorithms LUT-l and Edge-l), and background subtraction (Algorithm Subtr-l). 1. 26 For every conductive pattern, a logic value is measured for comparison with the expected value derived from CAD-based logic simula- 300 + 125°C + 75°C +25°C FORWARD CURRENT IN MICRO- 200 AMPERES (ELECTRON BEAM) 100 400 500 VF IN MILLIVOLTS 600 Figure 26.

Here, each pixel is enlarged in all directions to obtain an enlarged pattern. This enlarged pattern is then contracted by the same amount. Such processing eliminates small convex features, and the rest of the pattern is approximately restored. The small features will appear in an image subtraction between the raw picture and the enlarged-contracted picture. Similarly, small concave features may be detected by first contracting the input pattern. This scheme works especially well for binary patterns.

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