Two-handed hand gesture recognition for Bangla sign language using LDA and ANN

Rahat Yasir, R. Khan
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引用次数: 23

Abstract

Sign language detection and recognition (SLDR) using computer vision is a very challenging task. In respect to Bangladesh, sign language users are around 2.4 million [16]. In this paper, we try to focus for communicating with those users by computer vision. In this respect, an efficient method is proposed consists of some significant steps and they are, skin detection, preprocessing, different machine learning techniques like PCA and LDA, neural network for training and testing purpose of the system. Various hand sign images are used to test the proposed method and results are presented to provide its effectiveness.
基于LDA和ANN的孟加拉手语双手手势识别
使用计算机视觉进行手语检测和识别是一项非常具有挑战性的任务。孟加拉国的手语使用者约为240万[16]。在本文中,我们试图将重点放在通过计算机视觉与这些用户进行通信上。在这方面,提出了一种有效的方法,包括一些重要的步骤,它们是皮肤检测,预处理,不同的机器学习技术,如PCA和LDA,用于系统训练和测试目的的神经网络。使用不同的手势图像对所提出的方法进行了测试,并给出了测试结果,以证明该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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