본 논문에서는 도로에서 주행 중인 차량검출 알고리즘에 대하여 연구한다. 카메라에서 입력된 영상으로부터 차량을 검출하기위해 먼저 분할 및 합병(split & merge)방법을 적용하여 영상을 분할하고 그 다음 분할된 영역을 해석하여 차량이 위치할 가능성이 높은 영역을 집중적으로 탐색하여 차량을 실시간으로 검출하는 알고리즘을 연구한다. 전방차량의 후면을 검출하기 위하여 수직/수평 성분을 특징으로 하였으며 적분영상을 이용하여 계산시간을 줄일 수 있는 Haar-like방법을 적용하였으며 분류기로는 SVM을 사용하였다. 제안된 방법의 성능을 평가하기 위해 350개의 영상을 사용하여 분류기를 학습하였으며, 또한 학습에 사용하지 않은 비학습영상 150개를 사용하여 인식률을 구하였다. 실험결과 비학습영상에 대해 95.00%의 인식률을 얻었다.
KSP Keywords
Haar-like
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