The Study Of Methods About Face Detection In Complicated Condition

Face detection is a very important step before the face recognition. The size and the location of the face are detected in the process. With the rapid development of science and technology, as well as people's demand for pattern recognition and computer-based interactive development, human face detection technology has also developed so quickly.The methods of face detection in complicated condition based on the current methods have been done some research in the paper. A new illumination compensation method which be called fuzzy adaptive light compensation has proposed and the effect of the segmentation and lip detection has improved in the paper. And new rectangle features have added to train a new classifier here.The main contributions are as followed:Complexion is an important character of face. Avoiding the effect of the light, a new light compensation method which uses the fuzzy adaptive light compensation has proposed to enhance the quality of the image, so it is easier to do the binarization.Then segmentation has been done by Gauss model in YCbCr space. Then the image has been binarized based on the OUST and threshold adjustment. When detecting the lip, a new detection standard has proposed based on the combination of two current methods.AdaBoost is a very popular method to do the face detection. New three rectangle features has been added and a classifier has been trained by both the old and new rectangle features. Then put the new classifier into the program and detect the human face.At last, a new method based on the current two methods was proposed, through analyzing the advantages and disadvantages of the current methods.The experiment proves that the method is effective and has a good performance.