A Wavelet-Based Approach in Detecting Visual Defects on Semiconductor Wafer Dies

The objective of this paper is to implement a two-dimensional wavelet transform (2-D WT) approach for detecting visual defects such as particles, contamination, and scratches on semiconductor wafer dies. The gray image of 1/20 of a wafer die is initially processed by smooth and high-pass filters. Then, it is decomposed directly by 2-D WT at multiple scales and different wavelet bases. The interscale ratio from the wavelet transform modulus sum (WTMS) across adjacent decomposition levels (scales) for suspicious pixels on a wafer die is calculated. Since irregular edges in a small domain preserve much more wavelet energy, an edge pixel potentially belongs to a visual defect if its interscale ratio is less than a predefined threshold. The proposed approach is template-free and is easy to implement, so it is suitable for more product varieties and small-batch production. Real wafer dies with synthetic defects are used as testing samples to evaluate the performance of proposed approach. Experimental results from a small amount of testing samples show that the proposed method is able to identify particle, contamination, and scratch defects without missed detection and false alarm by appropriate choice of wavelet bases, scale, and image resolution. The proposed inspection approach could be considered as a potentially precise and low detection error method for further large amounts of inspections in a real environment.