A Novel Approach Using a Two-Dimensional Wavelet Transform in Ball Grid Array (BGA) Substrate Conducting Path Inspections

This paper presents a novel approach for localising open and short boundary defect candidates on ball grid array (BGA) substrate conducting paths by using a 2D wavelet transform (2D WT). Once the potential defects are identified, traditional printed circuit board (PCB) inspection algorithms can focus on these candidates for further analysis to identify true open and short defects. The defect-detecting scope and the inspection effort are thereby significantly reduced. The binary BGA substrate image is processed. It shows only the boundaries of BGA substrate conducting paths, which are further decomposed directly by 2D WT. Since most of the wavelet energy is clustered at the edges of image objects, the wavelet transform modulus sum (WTMS) of each edge pixel on BGA substrate conducting path boundaries is initially collected. By comparing the WTMS of an edge pixel on decomposition level j with its WTMS on an adjacent decomposition level j+ 1, an across-level ratio can be estimated to verify the irregularity of an edge pixel. That is, an edge pixel is classified as strongly irregular (e.g. potential open or short defects) if its across-level ratio reaches a predefined threshold. The proposed approach is template-free and easy to implement, so it is suitable for small-batch production. Real BGA substrates with synthetic boundary defects are used as test samples to evaluate the performance of the proposed approach. Experimental results show that the proposed method is capable of capturing all the open and short defects on BGA substrate conducting paths without missing any errors by using a selected across-level ratio threshold and appropriate decomposition level.