Template Matching Algorithm Implementation For Introduction To Indonesian Traditional House

  • Agus Sujarwadi UTY
  • Joseph Carlo K Universitas Atma Jaya Yogyakarta
  • Iwan Hartadi TU Universitas Teknologi Yogyakarta
  • Erik Iman HU Universitas Teknologi Yogyakarta
  • Suhirman Universitas Teknologi Yogyakarta
  • A.Djoko Budiyanto Universitas Atma Jaya Yogyakarta
  • Suyoto Universitas Atma Jaya Yogyakarta
  • Natan Derek National Taiwan Normal University, Taiwan
Keywords: Digital Image Processing, Pattern Recognition, Template Matching Method


Digital image processing is an important way in computer vision to determine the shape of digital image objects. Many image processing applications have been produced, one of which is pattern recognition. Pattern recognition can be interpreted as the process of classifying a number of objects into several categories based on similarities and similarities in characteristics. In this study, the pattern recognition of traditional houses in Indonesia will be carried out. In the pattern recognition process, several stages of image processing (image pre-processing) are needed which aims to make the pattern obtained can be recognized accurately. For the introduction of this traditional house, several stages will be carried out before it can finally be recognized by the system. First, the image will be converted into a gray image, after the gray image is obtained, it will be converted into a binary image using thresholding and then followed by normalizing the image size (resize). After that, the resized image will be recognized using the Template Matching method. The results of this study, using 20 examples of traditional house patterns categorized into 10 types of traditional houses in Indonesia, the system can recognize 16 traditional house patterns correctly with an accuracy percentage of 80%. But this system also still has imperfections. Imperfections occur due to several factors such as taking the angle of the object in the test image that does not match the angle of the object in the target image, and also the presence of additional objects that cover the shape of the traditional house that will be recognized; such as: trees, cars, etc., as well as poor test image conditions.


Kanan C, Cottrell GW, Color-to-Grayscale: Does the Method Matter in Image Recognition? PLoS ONE 7(1): e29740. doi:10.1371/ journal.pone.0029740, 2012

Krinidis, S, Krinidis, M and Chatzis,V, International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 5, No. 2, June, 2012

Bhattacharya, D, and Maity, AB., A Study on Vehicle Number Plate Identification by Morphological Edge Detection and Template Matching, International Journal of Information and Education Technology, Vol. 1, No. 3, August 2011

Bhoi, N and Mohanty, MN., Template Matching based Eye Detection in Facial Image, International Journal of Computer Applications (0975 – 8887), Volume 12– No.5, December 2010

Tinghua, A, Cheng,X, Liu, P., and Yang, M, A shape analysis and template matching of building features by the Fourier transform method, Computers, Environment and Urban Systems, Volume 41, September 2013, Pages 219–233

Acharya, T,and Ray, A, Image processing: principles and applications WileyInterscience, 2005.

Gonzalez, R.C.; Woods, R.E., Digital Image Processing. Prentice Hall, 2002.

How to Cite
Agus Sujarwadi, Joseph Carlo K, Iwan Hartadi TU, Erik Iman HU, Suhirman, A.Djoko Budiyanto, Suyoto, & Natan Derek. (2022). Template Matching Algorithm Implementation For Introduction To Indonesian Traditional House. International Journal of Engineering Technology and Natural Sciences, 4(2), 142 - 148. https://doi.org/10.46923/ijets.v4i2.182