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Timor Leste Tais Motif Recognition Using Wavelet and Backpropagation

机译:小波和反向传播的东帝汶泰斯图案识别

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Timor Leste is a new country of the 21st century in Southeast Asia that has a diverse culture. Tais Timor Leste has a high historical value as well as cultural identity. It is also one of the cultural heritages of Timor Leste. Tais Timor has its own characteristics and meanings in every motif, but there are still many communities of Timor Leste as well as foreign tourists who do not know the variety of the motif. Therefore, this study aimed to establish the system recognition of Tais Timor motif through the image based on the type of motif. The wavelet transform is used in the process of feature extraction and image decomposition to obtain coefficient values of which the value of energy and entropy will then be calculated. For the recognition of Tais Timor motif, backpropagation algorithm was used. This application is built using MATLAB pro-gramming language. The analysis and testing of these studies show that the accuracy of recognition of Tais Timor motif with 4 testing parameters got recognition accuracy and presentation of 80%. Thus the motif used can be identified by using both wavelet transform and backpropagation algorithm.
机译:东帝汶是二十一世纪东南亚的一个新兴国家,有着多元的文化。 Tais Timor Leste具有很高的历史价值和文化认同。它也是东帝汶的文化遗产之一。泰晤士帝汶在每个图案中都有其自身的特征和含义,但是仍然有许多东帝汶社区以及外国游客不知道该图案的多样性。因此,本研究旨在通过基于主题类型的图像来建立大帝汶主题的系统识别。小波变换用于特征提取和图像分解的过程中,以获取系数值,然后计算其能量和熵的值。为了识别Tais Timor主题,使用了反向传播算法。该应用程序是使用MATLAB编程语言构建的。对这些研究的分析和测试表明,具有4个测试参数的Tais Timor基序的识别准确度达到了80%。因此,可以通过同时使用小波变换和反向传播算法来识别所使用的图案。

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