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Face Sketch Multiple Features Detection Using Simultaneously Shape and Landmark Movement

机译:面部素描多个功能检测使用同时形状和地标运动

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Nowadays, retrieving a person identity using a photograph from the face image database is a crucial job especially in police investigations. Unfortunately in many cases, the photo image of a suspect is not available. Only a face sketch drawing based on the recollection of an eyewitness is available. Usually, there are two kind of face sketches employed in police investigations i.e. halftone face sketches. In this paper, we propose a modified line gradient method called Maximum Line Gradient Method to detect multiple features from halftone face sketches by using simultaneously moving shapes and landmarks. Our proposed method is divided into four stages: training, create image gradient, shape initialization, and multiple features detection processes. The last stage is started by searching the maximum line gradient value between two landmarks. Thus, by using the Similarity Transformation Equation, the set of landmarks (shape) will be simultaneously moved. The position of new landmark is enhanced by using simultaneously landmark movements on each shape. In the experiment, we employ 50 halftone face sketches which being examined by using 7 features with 38 landmarks. Our propose method demonstrates that the detection accuracy is 92.16%.
机译:如今,使用来自面部图像数据库的照片检索人身份,这是一个重要的工作,特别是在警察调查中。不幸的是,在许多情况下,嫌疑人的照片图像不可用。只有基于目击者的回忆的面素描图。通常,警察调查中采用了两种脸草图,即半色调脸草图。在本文中,我们提出了一种改进的线梯度方法,称为最大线梯度方法,通过使用同时移动形状和地标检测半色调面谱的多个特征。我们提出的方法分为四个阶段:培训,创建图像梯度,形状初始化和多个特征检测过程。通过搜索两个地标之间的最大线梯度值来开始最后阶段。因此,通过使用相似性转换方程,将同时移动该组地标(形状)。通过在每个形状上使用同时具有地标移动来增强新地标的位置。在实验中,我们使用了50个半色调的面部草图,通过使用具有38个地标的7个功能来检查。我们的提议方法表明检测精度为92.16%。

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