An Implementation of Hamming Code on Marker Based Augmented Reality for Introducing Local Wisdom of Batik
Wiwid Widyanto, Rosa Ariani Sukamto, Isma Widiaty, Alejandro Rosales Pérez, Lala Septem Riza
Universitas Pendidikan Indonesia, Bandung, Indonesia
School of Engineering and Science, Tecnologico de Monterrey, Monterrey, Mexico
Abstract
Batik is a fabric made with anti-wax dyeing techniques and is one of the many cultural heritage of Indonesia that has high artistic value and has become the hallmark of a nation that must be preserved. One way to preserve it, is to introduce batik. In order to make it more attractive, we can use multimedia as media to introduce batik. Augmented reality (AR) is a technology that adds virtual objects into the real world. This technology could provide a new way of delivering information to users, which is more interactive. So, it is expected to increase the sense of desire to know batik and its local wisdom. In this research, a system of marker-based tracking AR used to introduce batik and its local wisdom (called batikAR) was made. One type of AR is marker-based tracking methods. These methods use a marker as a reference display objects/ information. To track markers, there are several steps that must be performed on every frame received from the camera android smartphone. The phase of tracking in this study includes: conversion of images from the camera frame into a grayscale image, thresholding, the contour detection, perspective transformations, and finally decoding using the Hamming Code algorithm. According to the experimentations that were conducted, user responses to the application batikAR are good enough. Moreover, tracking markers on this system could properly track 100% of each marker in normal circumstances, within a certain range depending on the size of the marker and at an angle of 450. However it is unaffected by ambient light conditions. Therefore, we can state that the system can be used as an alternative teaching methods for introducing batik and its local wisdom.
Keywords: Image processing, Augmented reality, Local Wisdom, Learning media
Topic: Computer Science Education