基于面部的实时应用性别分类

Q4 Environmental Science Iranian Journal of Botany Pub Date : 2022-06-16 DOI:10.33897/fujeas.v3i1.506
Muhammad Imran, Anmol Haider
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引用次数: 0

摘要

外貌和面部特征在通过图像进行性别识别中起着重要的作用。为了获得更好的性别分类效果,提出了多种技术,其中预处理是性别分类的主要和重要部分之一,它可以去除图像中的噪声,增强图像,消除图像中的不自然颜色。另一个主要方面是高效的特征提取方法。如果特征提取准确,分类结果将得到改善。在过去的几年里,性别分类技术在受控环境下工作得很好。然而,由于低分辨率、偏离角度的姿势、遮挡和各种表情,实时应用出现了挑战。本研究的主要重点是克服现有的挑战,提出一种可以在实时应用中实现的方法。本研究提出了一种新颖的方法,将CNN用于实时应用的性别分类。为了评估所提出方法的性能,在静态图像和视频数据集上进行了实验。所提出的研究工作在实验中达到了98%的准确率。
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Facial Based Gender Classification for Real Time Applications
Appearance and facial features play an important role in gender recognition through images. For gender classification, multiple techniques were presented to acquire better results in which preprocessing part is one of the major and very important for gender classification as it removes noise, enhances, images, and eliminates any unnatural colors from an image. Another major aspect is the efficient feature extraction method. If features extracted accurately then the result of classification will improve. Over the past few years, gender classification techniques work perfectly for a controlled environment. However, challenges occurred for real-time applications due to low resolution, off-angle poses, faces with occlusion, and various expressions. The main focus of this study is to overcome existing challenges and propose a method that can be implemented in real-time applications. This research work proposed a novel method in which CNN has been used for classification of gender for real-time application. To assess the performance of proposed method experiments were conducted on static images and video data sets.  The proposed research work achieved 98% of accuracy during the experiments.
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来源期刊
Iranian Journal of Botany
Iranian Journal of Botany Environmental Science-Ecology
CiteScore
0.80
自引率
0.00%
发文量
0
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