Face Detection Using Shapes and Colors in Various Backgrounds

Chang-Hyun Lee; Hyun-Ji Lee; Seung-Hyun Lee; Joon-Taek Oh; PARK SEUNGBO

doi:10.9708/jksci.2021.26.07.019

In this paper, we propose a method for detecting characters in images and detecting facial regions, which consists of two tasks. First, we separate two different characters to detect the face position of the characters in the frame. For fast detection, we use You Only Look Once (YOLO), which finds faces in the image in real time, to extract the location of the face and mark them as object detection boxes. Second, we present three image processing methods to detect accurate face area based on object detection boxes. Each method uses HSV values extracted from the region estimated by the detection figure to detect the face region of the characters, and changes the size and shape of the detection figure to compare the accuracy of each method. Each face detection method is compared and analyzed with comparative data and image processing data for reliability verification. As a result, we achieved the highest accuracy of 87% when using the split rectangular method among circular, rectangular, and split rectangular methods.

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* 2021년 이후 발행 논문의 참고문헌은 현재 구축 중입니다.

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이 논문은 한국연구재단의 지원을 받아 작성되었습니다.

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