Rapidly Void Detection in TSVs With 2-D X-Ray Imaging 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. Voids may be produced during via filling; therefore, void detection is important for improving the quality of 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 blocks for multithreshold image cutting and feature extraction. An artificial neural network (ANN) was then used to find the blocks that contain voids, and the voids were located by Hough transform. The effects of various block widths and heights were studied; a block size of 30×40 pixels 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.