2014
DOI: 10.1007/s10845-014-0924-5
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Automatic optical inspection system for IC molding surface

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Cited by 60 publications
(20 citation statements)
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“…The existing surface defect detection methods based on machine vision can be classified into four categories in term of texture surface features: 1) non-textured surface; 2) repeated pattern surface; 3) homogeneouslytextured surface;4) non-homogeneously-textured surface. For non-textured surface images, such as sheet steel [2] [3], glass screen [5] or integrated circuit [5] ,the commonly used texture features are statistical measures [6], for instance first-order statistics (i.e., mean and variance) and second-order statistics [7]. For repeated pattern surface images, such as textile fabrics [8]., semiconductor wafers [9]..…”
Section: Related Work On Solar Cell Surface Detectionmentioning
confidence: 99%
“…The existing surface defect detection methods based on machine vision can be classified into four categories in term of texture surface features: 1) non-textured surface; 2) repeated pattern surface; 3) homogeneouslytextured surface;4) non-homogeneously-textured surface. For non-textured surface images, such as sheet steel [2] [3], glass screen [5] or integrated circuit [5] ,the commonly used texture features are statistical measures [6], for instance first-order statistics (i.e., mean and variance) and second-order statistics [7]. For repeated pattern surface images, such as textile fabrics [8]., semiconductor wafers [9]..…”
Section: Related Work On Solar Cell Surface Detectionmentioning
confidence: 99%
“…Hence there is a clear need for an automatic threshold method which is able to separate out cracks in the microstructure as a separate phase. Several methods to identify cracks or defects based on images have been developed for inspection purposes [17,18], however, these methods do not consider SEM images and are typically focused on identifying single cracks in simple uniform bodies rather than extracting a crack network from a cross section.…”
Section: Image Segmentationmentioning
confidence: 99%
“…The spatial dispersions between the texture and the high‐energy components are related. The literature reports that DFT and DWT have been validated in applications to detect defects in regular textures and statistical textures [10–13]. DCT has only been validated for applications to detect defects in regular texture [14], and there is very little literature about its application in statistical textures.…”
Section: Literature Reviewmentioning
confidence: 99%