Face detection using color segmentation and RHT

Aminian, Ali; Beni, Mohammad Salimi

doi:10.1109/pria.2017.7983032

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…An ellipse is also used for face detection because in general human faces are elliptical, so detection is right on the face area [8]. There is a research that discusses about ellipse detection in images using Randomized Hough Transform (RHT) [9].…”

Section: Related Workmentioning

confidence: 99%

Face Detection Using Randomized Hough Transform (RHT) with Various Ellipses Segmentations

Fachrurrozi,

Saparudin,

Mardiana

et al. 2020

SJIA

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Face detection is one of earlier phase in face recognition process. This research aims to get the faces area on digital image without being affected by face orientation, lights condition, background and the expression. The detected face area is usually shaped by a rectangle. Many pixels on the rectangle are not part of face, especially at the four of the image corners. This research use an ellipse as replacement a rectangle. The detected face is shaped by ellipses with various sizes and orientations. The digital image segmentations is used to detect face candidates area. The ellipse is formed by using Randomized Hough Transform (RHT) method, which is influenced by the center point of ellipse candidates. RHT found three random pixels on segmented image. The rate of success of RHT is determined by segmentation results. The research result is tested by using various thresholds, and get the best accuracy at 74.4%. The rate of accuracy is measured by comparing between RHT ellipses shape and circle shape on OpenCV library as ground truth.

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Section: Related Workmentioning

confidence: 99%

Face Detection Using Randomized Hough Transform (RHT) with Various Ellipses Segmentations

Fachrurrozi,

Saparudin,

Mardiana

et al. 2020

SJIA

View full text Add to dashboard Cite

show abstract

“…Recent studies that combined face segmentation and face recognition technology have provided an important concept for our research. For example, one study extracted face-like regions by using the extracted color information of an image in HSV color space, and the RHT algorithm is then applied to find face region [13]. Samantha proposed a technology of segmentation skin color through YcbCr as well, then applied artificial neural network classified face and non-face classes [14].…”

Section: Introductionmentioning

confidence: 99%