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Effectiveness of Haar wavelet and grayscale features in different illumination for facial features detection

机译:Haar小波和灰度特征在不同光照下对面部特征检测的有效性

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Wavelet is widely used in signal processing field. As the simplest wavelet framework, Haar wavelet is very popular dueto its memory efficient, fast and easy to implement. Haar wavelet can be employed to process the image for furtherpurpose like image compression. In this paper, the effectiveness of Haar wavelet and grayscale features are evaluated byemploying template matching as the principle technique. Results show that Haar wavelet feature is more relevant infacial feature detection task as compared to grayscale feature.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
机译:小波被广泛应用于信号处理领域。 Haar小波作为最简单的小波框架,由于其高效的存储,快速且易于实现的功能而非常受欢迎。 Haar小波可用于处理图像,以实现进一步的目的,例如图像压缩。本文以模板匹配为主要技术,对Haar小波和灰度特征的有效性进行了评价。结果表明,与灰度特征相比,Haar小波特征与人脸特征检测任务更为相关。©(2012)COPYRIGHT光电仪器工程师协会(SPIE)。摘要的下载仅允许个人使用。

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