An efficient algorithm for detecting spherical particles from differential interference microscopic images
2017 · Measurement Science and Technology
저자
Hyeyoung Hong, 남재욱 (Jaewook Nam)
연구주제
Industrial Vision Systems and Defect Detection
NTIS 과학기술표준분류
가장 가까운 분류(재료 > 분석/물성 평가기술)가 화학·화공 범위 밖이다. 배정 근거: 지원 과제·키워드 근거가 없어 AI가 논문 제목·초록을 읽고 고른 분류.
AI 연구 키워드·방법
anisotropic conductive film particulate film spherical particle detection
키워드 (OpenAlex)
differential interference contrast microscopy anisotropic conductive film image analysis algorithms
초록
Abstract Particulate films have become critical parts in electronics industries because they can provide the required optical and electrical properties. Microstructures, which consist of various particles inside the films, strongly influence the performance of devices. Therefore, the visualization and detection of particles can be an indirect method of determining the device performance without destroying samples. In this study, we propose an image analysis algorithm to detect spherical particles inside a thin film visualized by a differential interference contrast microscope. Our goal is to develop a robust and efficient algorithm specifically for uniform-sized spherical particles sandwiched between two solid thin and flat plates, which are usually applied in anisotropic conductive films that provide electrical and mechanical connections between two electrodes from a chip and substrate.…
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교수 1
연구주제 1
Industrial Vision Systems and Defect Detection