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Face detection is a significant research topic to recognize the identity for many automated systems. In this paper, we propose a face detection algorithm to detect a single face in an image sequence in the real-time environment by finding unique structural features. The proposed method allows the user to detect the face in case the lighting conditi...
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... Roberts cross gradient operator is used in our proposed approach to estimate the magnitude of the gradient of the test image. The main advantages of using Roberts cross operator in our approach are: simplicity, applicability of spatial gradient measurements on two-dimensional images and computing masks of size 2 × 2 which needs fewer computations. The regions of high special frequency will be highlighted. These regions often correspond to edges of the face. Several face detection approaches can detect different ethnic groups [14]. The pigments carotene, hemoglobin, and melanin involved in skin color are varying among people. Hence, skin color can be considered as a robust feature to detect human faces. Also, skin color feature allows fast processing. Our proposed approach is shown in Figure 3. It includes two levels to detect a single face. In the first level, the system uses skin color as a feature for face detection. To achieve that, the camera captures 2 frames every 1 second. The algorithm calculates the RGB color for each pixel in the captured frame. After that, the RGB color space is converted to YC b C r color space. The newly obtained YC b C r color frame is decomposed into 3 separate layers of Y, C b and C r components respectively. The proposed approach has the advantage of creating an interaction between the user and the computer. The user can choose between multiple options which are Face Detection option, Environment Detection option and Luminance option, which is the face detection in varying light conditions. In the normal lighting conditions, the algorithm detects the face depending only on the value of Cr to get more accurate results and not the combination between the three color channels. To achieve this goal, user has to choose Face detection option in the GUI. The value of C r should be in the range between two threshold values; T1 and T2 respectively. After extensive experimentation, we found that the best threshold value for C ...
