| Citation: | XU Shou-long, WANG Zhi-lin, HUANG You-Jun, LI Qing-Xin, ZOU Shu-liang. Ionizing Particle Discrimination and Extraction Based on Morphological Imaging Features[J]. Chinese Optics. doi: 10.37188/CO.2025-0134
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To reduce pulse pile-up and improve ionizing particle discrimination efficiency. This study uses a CMOS active pixel sensor to analyze ionizing particle optical responses and propose morphology-based discrimination. Particle response features were compared to reveal gain and integration effects, and discrimination effectiveness was validated. Results show α events differ significantly from β and γ events in pixel count, mean pixel value, rectangularity, convexity, and compactness. β and γ events are similar in pixel count, rectangularity, and convexity, but differ in mean pixel value or compactness. Using pixel count, α events were identified with over 99% accuracy. β and γ events were discriminated by mean pixel value with over 82% accuracy. The results provide a new method and basis for ionizing particle identification in mixed radiation fields. It supports nuclear particle discrimination and noise mitigation, providing new approaches and theoretical guidance.
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