The Implementation of Augmented Reality Hairstyles at Beauty Salons Using the Viola-Jones Method (Case Study: Eka Salon)

Graha Virgian Gustira Putri, Ade Syahputra, Silvester Dian Handy Permana


Augmented reality is the technology that superimposes a computer-generated digital content on a user's view of the real world in a real time so users can experience the real virtual objects. The use of augmented reality has spread into various industries, for an example in the fashion industry. One of fashion industry type is hairstyle industry. Eka Salon is a beauty salon that provides beauty treatments for women's hair care. This salon has a problem that customer are not satisfacted with the results of their new haircut because that doesnt match with their expectations. This can be seen from the results of observations at Eka Salon is resulted that 8 out of 15 interviewed customers were not satisfied with their new haircuts because it did not match the appearance in the catalog. In this research, an augmented reality hairstyles will be made that can visualize how the shape of the selected hairstyle by the customer without having to cut their hair first. The Viola-Jones method was chosen as the method used in this study because it has a high accuracy of 90% in face detection. The result of this research is that the Viola-Jones method can detect facial surfaces and generate a 3D hairstyle model distance to 100cm properly. The test of the acceptance level of this application is carried out by Eka Salon customers with an average percentage of 84.3%.


Augmented reality; Viola-jones; Simulation; Hairstyles

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Brianorman, Y., & Komputer, J. S. (2015). METODE EIGENFACE PADA SISTEM ABSENSI. Sistem Komputer Untan, Volume 03 No. 1 : 41-50

Damanik, R. R., Sitanggang, D., & Pasaribu, H. (2018). An application of viola jones method for face recognition for absence process efficiency An application of viola jones method for face recognition for absence process efficiency. Conference Series PAPER: 0–8.

Dan, D., Fitur, R., & Pada, M. (2015). CITRA WAJAH MENGGUNAKAN HAAR CASCADE. IDeaTech 2015: 298–305.

Hbali, Y., Ballihi, L., Sadgal, M., & Abdelaziz, E. F. (2016). Face Detection for Augmented Reality Application Using Boosting-based Techniques. International Journal of Interactive Multimedia and Artificial Intelligence, Vol. 4: 22-28.

Huang, J., Shang, Y., & Chen, H. (2019). Improved Viola-jones face detection algorithm based on HoloLens. Huang et al. EURASIP Journal on Image and Video Processing ,Vol.6.

Kirana, C. (2016). Face Identification For Presence Applications Using Violajones and Eigenface Algorithm. SISFOKOM, Vol.5: 7–14.

Kurdy, M. (2018). EMOTION RECOGNITION USING FACIAL EXPRESSION. Journal of Theoretical and Applied Information Technology, Vol.96. No 18 : 6118-6129.

Paul, T., Shammi, U. A., Kobashi, S., & Detection, M. F. (2018). A Study on Face Detection Using Viola-jones Algorithm in Various Backgrounds, Angles and Distances. Biomedical Soft Computing and Human Sciences, Vol.23, No.1, pp.27-36.

Prasetya, D. A., & Nurviyanto, I. (2012). Deteksi wajah metode viola jones pada opencv menggunakan pemrograman python. Simposium Nasional RAPI XI FT UMS: 18–23.

Priyadharsini, G. R., & Krishnaveni, K. (2016). An Analysis of Adaboost Algorithm for Face Detection. Indian Journal of Science and Technology, Vol 9(19) :1-4.

Putro, M. D. (2012). Sistem Deteksi Wajah dengan Menggunakan Metode Viola-Jones. Science, Engineering and Technology 2012 : 1-5.

Rian, R., Putra, C., Juniawan, F. P., Studi, P., Informatika, T., & Analysis, L. D. (2017). PENGENALAN WAJAH PADA SISTEM KEHADIRAN MAHASISWA BERBASIS ANDROID, Jurnal Telematika Vol. 10 No. 1 : 132- 146.

Singh, V., Shokeen, V., & Singh, B. (2013). FACE DETECTION BY HAAR CASCADE CLASSIFIER WITH SIMPLE AND COMPLEX BACKGROUNDS IMAGES USING OPENCV IMPLEMENTATION. International Journal of Advanced Technology in Engineering and Science, Volume No.01: 33-38.

Tripathi, R. C. (2011). R EAL T IME F ACE R ECOGNITION U SING A DA B OOST I MPROVED F AST PCA A LGORITHM. International Journal of Artificial Intelligence & Applications (IJAIA), Vol.2, No.3 : 46- 58.

Zul, M. I., Muslim, I., & S, A. K. (2017). Identifikasi Bentuk Frame Kacamata dengan Metode Pengukuran Pixel dan Algoritma k-NN. Jurnal Infotel Vol.9 No.4 : 429-435.



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Journal Name: JISA (Jurnal Informatika dan Sains)
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