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首页> 外文期刊>Jurnal RESTI: Rekayasa Sistem dan Teknologi Informasi >Klasifikasi Kelompok Usia Melalui Citra Wajah Berbasis Image Texture Analysis pada Sistem Automatic Video Filtering
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Klasifikasi Kelompok Usia Melalui Citra Wajah Berbasis Image Texture Analysis pada Sistem Automatic Video Filtering

机译:基于图像纹理分析对自动视频滤波系统的脸部图像的年龄组分类

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摘要

Nowadays information technology makes it easier for everyone to access various information, this easiness harms minors, because it is possible to access adult content from the internet, television or mobile devices. The problem is the unavailability of the system for filtering and authentication to get information by the face. The face contains information related to personal characteristics such as age, etc. feature extraction is an important stage in the face recognition process. This study proposed local binary pattern (LBP) and gray level co-occurrence matrix (GLCM) as feature extraction to describe face feature, and we use artificial neural network to classify the human age, the experiment result after calculation with confusion matrix obtained average acceleration of 94.8%, precision of 93.7% and recall of 92.3%, it’s performance measure obtained proposed method can be described face feature it well, so that, the proposed method can be used as reference material to development video filtering system by age of the users in access information based on video especially pornography and violence content.
机译:如今,信息技术使每个人都更容易访问各种信息,这种容易危害未成年人,因为可以从互联网,电视或移动设备访问成人内容。问题是系统用于过滤和认证以获取面部信息的不可用。面部包含与年龄的个人特征有关的信息等。特征提取是面部识别过程中的一个重要阶段。本研究提出了局部二进制模式(LBP)和灰度级共发生矩阵(GLCM)作为特征提取来描述面部特征,并且我们使用人工神经网络来分类为人类时代,用困惑矩阵计算后的实验结果获得平均加速度94.8%,精度为93.7%,再调用92.3%,它的性能措施获得了所提出的方法,可以描述面部的特点,这样,所提出的方法可以用作用户的参考资料到开发视频过滤系统的年龄基于视频的访问信息,尤其是色情和暴力内容。

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