Timor Leste Tais Motif Recognition Using Wavelet and Backpropagation

SOARES, VASIO SARMENTO and Santoso, Albertus Joko and Setyohadi, Djoko Budiyanto (2017) Timor Leste Tais Motif Recognition Using Wavelet and Backpropagation. In: 2017 International Conference on Soft Computing, Intelligent System and Information Technology ICSIIT 2017. Petra Christian University, Bali, Indonesia, pp. 45-50.

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Text (Vasio Sarmento Soares, Albertus Joko Santoso and Djoko Budyanto Setyohadi) 50. Timor leste tais motif recognition using wavelet and backpropagation.pdf Download (2MB) | Preview

Abstract

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 programming 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.

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