Void Detection in TSVs With X-Ray Image Multithreshold Segmentation and Artificial Neural Networks.

Through-silicon via (TSV) is a vertical channel that passes through a chip to connect stacked dies in 3-D packaging. Void may be produced during the high aspect ratio TSV filling process with copper electroplating method. Therefore, void detection becomes an important aspect for high-quality TSV devices. In this paper, a rapid void detection method using a single 2-D X-ray imaging was developed. An image processing method was used to divide the X-ray image into some small blocks for multithreshold image cutting and feature extraction. An artificial neural network was then used to find and locate the blocks that contain voids. The effects of segmentation threshold, various block widths, and heights were studied; a block size of \(30 \times 40\) pixels (width \(\times \) height) is recommended. The void detection is more sensitive to block width than height. Experiments show that the method proposed in this paper can automatically and rapidly detect voids in TSVs using one 2-D X-ray image. [ABSTRACT FROM AUTHOR]