Research and application of Haar-like feature-based face detection algorithm
With the continuous development of social informatization and intelligentization,face detection technology has gradually become a hot topic in the field of target detection.Research methods include literature research and theoretical analysis.The Haar-like feature-based AdaBoost face detection algorithm used in this paper,combined with the OpenCV computer vision open-source library,aims to efficiently detect potential face areas in target images.Haar-like features describe target shape charac-teristics using black-and-white areas in the image,and when combined with the AdaBoost algorithm,they can improve the accuracy and robustness of face detection.The use of the OpenCV open-source library makes the algorithm more convenient and efficient to implement.Experimental results have shown that the AdaBoost face detection algorithm based on Haar-like features can not only improve the detection rate of face images,but also significantly shorten the face detection time,which has high practical value.Therefore,the research and application of the Haar-like feature-based AdaBoost face detection algorithm are of great significance in promoting the development of face recognition technology.
face detectionHaar-like featuresAdaBoost algorithmOpenCV computer vision open-source library
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