文献类型：期刊文献

英文题名：Neutrosophic set-based defect detection method for CSP LED images

作者：Fan, En[1];Gong, Junqi[1];Wu, Zhenxin[1];Lv, Qinlong[1];Fan, Changxing[1]

机构：[1]Shaoxing Univ, Inst Artificial Intelligence, Shaoxing, Peoples R China

年份：2025

卷号：13

外文期刊名：FRONTIERS IN PHYSICS

收录：SCI-EXPANDED(收录号：WOS:001564004400001)、、EI(收录号：20253619116864)、Scopus(收录号：2-s2.0-105014920116)、WOS

基金：This work was supported by Grandseed Science & Technology Co. Ltd. through the provision of proprietary industry data.

语种：英文

外文关键词：chip scale package; position estimation; neutrosophic set; similarity operations; defect detection

外文摘要：Chip scale package (CSP) light-emitting diode (LED) is miniaturized light-emitting diodes designed for automated chip-level packaging. Defect detection is particularly challenging due to the high density and small size of CSP LED beads on a strip. This paper presents a neutrosophic set-based defect detection method (ND) to identify the defective beads on CSP LED images. Firstly, the proposed ND method applies the neutrosophic set to discribe the uncertainty in CSP LED images, and then converts the CSP LED images into the neutrosophic images. Moreover, it employs the similarity operation to handle the image noises and then utilizes an enhancement operation to enhance image contrast to ultimately generates smoother images. Finally, these smoother images are used to calculate the pass rates by checking the gray values. Experimental results demonstrate that the proposed ND method can accurately and reliably detect defective beads in CSP LED images across various exposure times. Moreover, it provides a more robust estimate of pass rate compared with five traditional detection methods.