Wafer Defect Detection Using Directional Morphological Gradient Techniques

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.