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Analysis of Straight Line Detection Using PCA

주성분 분석을 이용한 직선 검출에 대한 분석

  • Oh, Jeong-su (Department of Image Science & Engineering, Pukyong National University)
  • Received : 2015.06.10
  • Accepted : 2015.07.31
  • Published : 2015.08.20

Abstract

This paper analyzes the straight line detection using the principal component analysis (PCA) and proposes its improved algorithm to which two new functions are added. The first function removes invalid pixels through the detected straight line and detects a line again. The second function detects lines from non-overlapped blocks, selects valid line candidates, and detects a valid line from pixels adjacent to each line candidate. The proposed algorithm detects a more accurate straight line with a low computation in comparison with the conventional algorithm in an image with somewhat refined lines.

본 논문은 주성분 분석을 이용한 직선 검출 알고리즘을 분석하여 새로운 두 기능이 추가된 개선된 알고리즘을 제안한다. 첫 번째 기능은 검출된 직선을 통해 무효 화소를 제거하고 다시 직선을 검출하는 것이고, 두 번째 기능은 겹치지 않는 블록들에서 직선 검출을 통해 후보 직선들 선택하고, 각 후보 직선의 주변 화소들을 이용해 유효 직선을 검출하는 것이다. 제안된 알고리즘은 정제된 직선 영상에서는 기존 알고리즘보다 적은 계산량으로 더 정확한 직선을 검출하고 있다.

Keywords

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Cited by

  1. 주성분 분석과 허프 변환을 이용한 직선 검출 vol.22, pp.2, 2015, https://doi.org/10.6109/jkiice.2018.22.2.227