摘要
人脸识别是模式识别领域的一个具有挑战性的课题,并且有着潜在的应用前景。该文提出了基于DCT和神经网络的人脸识别方法,针对人脸图像分别提取整体和局部的DCT系数共同送入多层感知机分类器分类,实验表明所提出的方法具有识别速度快、识别率较高的综合优势。
Face recognition is a challenging task in the area of pattern recognition and has potential prospect for applications in the future. This paper proposes an approach based on the discrete cosine transform (DCT) and neural networks, which extracts holistic and local DCT coefficients and feeds them to the multi-layer perceptron classifier. The experiment shows the approach achieves a balanced tradeoff between recognition rate and speed.
出处
《计算机工程》
CAS
CSCD
北大核心
2004年第16期53-56,共4页
Computer Engineering
基金
国家自然科学基金资助项目
