A Novel Subpixel Detection Method for Surface Mount Devices with Dual-Row Asymmetric Pins

Vision inspection of surface mount devices is a crucial task in the operation of mounting machines. Components featuring dual-row asymmetrical pins pose a significant challenge in terms of identification due to their irregular and asymmetrical characteristics, exemplified by components like small outline transistor (SOT) and transistor outline (TO). These components exhibit variations in pin numbers, orientations, and sizes, necessitating users to provide extensive information for accurate identification using conventional methods. To address the need for fully automated recognition of dual-row asymmetric components with arbitrary orientations, a novel identification approach based on a pin search algorithm is proposed. This method comprises three main components: pin extraction, pin grouping, and subpixel refinement. Initially, connected component analysis technology is employed to extract all pins. Subsequently, a pin search algorithm is introduced, leveraging the positional and size relationships between pins to automatically detect potential pin distribution patterns. Finally, the Zernike moment method is utilized to enhance edge optimization to a subpixel level, thereby improving parameter accuracy. Experimental findings across various components demonstrate the efficacy of the proposed method in effectively resolving the identification challenges associated with dual-row asymmetric components at any orientation.