Abstract This paper proposes a novel adaptive technique to extract facial feature points automatically such as eyes corners, nostrils, nose tip, and mouth corners in frontal view faces, which are based on cumulative distribution function (CDF) approach by applying Otsu’s optimum global threshold value. At first, the method adopts the Viola-Jones face detector to detect the location of face and also crops the face region with forehead and without forehead areas in an image. The CDF of the cropped face region without forehead area is computed first by applying Otsu’s optimum global threshold value to create a new filtered face image in an adaptive way. According to concept of human face structure, the four relevant regions such as right eye, left eye, nose, and mouth areas are cropped from a filtered face image. The connected component of interested area for each relevant cropped filtered image is indicated as our respective feature region. A simple linear search algorithm for eyes and mouth filtered image and contour algorithm for nose filtered image are applied to extract our desired corner points automatically. The method was tested on three frontal face databases such as BioID, Nottingham and JAFFE with different illuminations, expressions and lighting conditions and the experimental results have individually achieved an average success rate of above 90%.