A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
CVGIP: Graphical Models and Image Processing
Computer Vision for Electronics Manufacturing
Computer Vision for Electronics Manufacturing
Computer and Robot Vision
Digital Image Processing
Directional morphological gradient edge detector
Directional morphological gradient edge detector
Machine Vision: Theory, Algorithms, Practicalities
Machine Vision: Theory, Algorithms, Practicalities
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Defect detection of IC wafer based on two-dimension wavelet transform
Microelectronics Journal
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Accurate detection and classification of wafer defects constitute an important component of the IC production process because together they can immediately improve the yield and also provide information needed for future process improvements. One class of inspection procedures involves analyzing surface images. Because of the characteristics of the design patterns and the irregular size and shape of the defects, linear processing methods, such as Fourier transform domain filtering or Sobel edge detection, are not as well suited as morphological methods for detecting these defects. In this paper, a newly developed morphological gradient technique using directional components is applied to the detection and isolation of wafer defects. The new methods are computationally efficient and do not rely on a priori knowledge of the specific design pattern to detect particles, scratches, stains, or missing pattern areas. The directional components of the morphological gradient technique allow direction specific edge suppression and reduce the noise sensitivity. Theoretical analysis and several examples are used to demonstrate the performance of the directional morphological gradient methods.