Efficient Selective Image Fusion: A PCB Diagnosis Approach and Implementation.

The document discusses an innovative approach to selective image fusion for PCB diagnosis, focusing on capturing high-resolution images of dense component areas. The method combines Transformer models and K-means clustering to enhance feature extraction and improve accuracy in component detection. Experimental results show significant improvements in detection accuracy and speed compared to traditional methods like SIFT. The study highlights the importance of selecting appropriate feature points for efficient and accurate image stitching, laying the groundwork for advancements in image processing technology. [Extracted from the article]