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Age Range Estimation Based on Facial Wrinkle Analysis Using Hessian Based Filter

机译:基于基于Hessian滤波器的面部皱纹分析的年龄范围估计

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Aging is a normal process that has an effect on different parts of the human body under the influence of various biological and environmental aspects. The most prominent changes that occur on the face are the form of the skin wrinkles, which are the main objective of this research. Specific wrinkle detection is an important task in face textural analysis. Previously, some researchers have been proposed the age range estimation based on wrinkle analysis in literature, but poor localization limits the performance of the whole age estimation process. This is because, when less number of wrinkles are detected or extracted, it will consequently affect the process to estimate the correct age. Therefore, we address this issue to enhance age range estimation method using a new approach to extract correct facial wrinkles for further analysis. We propose a method to extract facial wrinkle in face image using Hessian based filter (HBF) for age estimation. In other word, this research focus on age range estimation method based on facial wrinkle analysis extracted from facial image obtained from FG-NET database using hessian based filter. The proposed filter is theoretically straightforward, however, it significantly increases the wrinkle analysis result compared to previous methods. The result shows that HBF successfully obtained higher accuracy with over 90 % estimation rate.
机译:衰老是一个正常的过程,在各种生物学和环境方面的影响下,会对人体的不同部位产生影响。脸上最明显的变化是皮肤皱纹的形成,这是本研究的主要目的。特定的皱纹检测是面部纹理分析中的重要任务。以前,一些研究人员已经在文献中提出了基于皱纹分析的年龄范围估计方法,但是局域性差限制了整个年龄估计过程的性能。这是因为,当检测到或提取出较少数量的皱纹时,将因此影响估计正确年龄的过程。因此,我们解决此问题以使用新方法提取正确的面部皱纹以进行进一步分析来增强年龄范围估计方法。我们提出一种使用基于Hessian的过滤器(HBF)提取面部图像中的面部皱纹的方法,用于估计年龄。换句话说,该研究集中在基于面部皱纹分析的年龄范围估计方法,该面部皱纹分析是使用基于粗麻布的滤波器从FG-NET数据库获得的面部图像中提取的。所提出的过滤器在理论上很简单,但是,与以前的方法相比,它可以显着提高皱纹分析结果。结果表明,HBF成功地获得了较高的精度,估计率超过90%。

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