Gender Classification Using Viola Jones, Orthogonal Difference Local Binary Pattern and Principal Component Analysis

Muhammad Amirul Mukminin; Tio Dharmawan; Muhamad Arief Hidayat

doi:10.30812/matrik.v23i3.3879

Muhammad Amirul Mukminin Universitas Jember, Jember, Indonesia
Tio Dharmawan Universitas Jember, Jember, Indonesia
Muhamad Arief Hidayat Universitas Jember, Jember, Indonesia

DOI: https://doi.org/10.30812/matrik.v23i3.3879

Keywords: Gender Classification, Face Recognition, Viola Jones, Local Binary Pattern, Principal Component Analysis

Abstract

Facial recognition is currently a widely discussed topic, particularly in the context of gender classification. Facial recognition by computers is more complex and time-consuming compared to humans. There is ongoing research on facial feature extraction for gender classification. Geometry and texture features are effective for gender classification. This study aimed to combine these two features to improve the accuracy of gender classification. This research used the Viola-Jones and Orthogonal Difference Local Binary Pattern (OD-LBP) methods for feature extraction. The Viola-Jones algorithm faces issues in facial detection, leading to outliers in geometry features. At the same time, OD-LBP is a new descriptor capable of addressing pose, lighting, and expression variations. Therefore, this research attempts to utilize OD-LBP for gender classification. The dataset used was FERET, which contained various lighting variations, making OD-LBP suitable for addressing this challenge. Random Forest and Backpropagation were employed for classification. This research demonstrates that combining these two features is effective for gender classification using Backpropagation, achieving an accuracy of 93%. This confirms the superiority of the proposed method over single-feature extraction methods.

Downloads

Download data is not yet available.

References

[1] F. D. Adinata and J. Arifin, “Klasifikasi Jenis Kelamin Wajah Bermasker Menggunakan Algoritma Supervised Learning,” J. Media Inform. Budidarma, vol. 6, no. 1, p. 229, 2022, doi: 10.30865/mib.v6i1.3377.
[2] I. Adjabi, A. Ouahabi, A. Benzaoui, and A. Taleb-Ahmed, “Past, present, and future of face recognition: A review,” Electron., vol. 9, no. 8, pp. 1–53, 2020, doi: 10.3390/electronics9081188.
[3] M. J. Al Dujaili, H. T. S. Al Rikabi, N. K. Abed, and I. R. N. Al Rubeei, “Gender Recognition of Human from Face Images Using Multi-Class Support Vector Machine (SVM) Classifiers,” Int. J. Interact. Mob. Technol., vol. 17, no. 8, pp. 113–134, 2023, doi: 10.3991/ijim.v17i08.39163.
[4] A. Swaminathan, M. Chaba, D. K. Sharma, and Y. Chaba, “Gender Classification using Facial Embeddings: A Novel Approach,” Procedia Comput. Sci., vol. 167, no. 2019, pp. 2634–2642, 2020, doi: 10.1016/j.procs.2020.03.342.
[5] L. P. Zoo and E. Alliance, “Detection of Human Gender from Eyes Images Using DNN Approach,” vol. 17, pp. 336–340, 2021.
[6] Y. Kortli, M. Jridi, A. Al Falou, and M. Atri, “Face recognition systems: A survey,” Sensors (Switzerland), vol. 20, no. 2, 2020, doi: 10.3390/s20020342.
[7] Ulla Delfana Rosiani, Rosa Andrie Asmara, and Nadhifatul Laeily, “Penerapan Facial Landmark Point Untuk Klasifikasi Jenis Kelamin Berdasarkan Citra Wajah,” J. Inform. Polinema, vol. 6, no. 1, pp. 55–60, 2020, doi: 10.33795/jip.v6i1.328.
[8] A. Venugopal, Y. O. Yadukrishnan, and R. N. Nair, “A SVM based Gender Classification from Children Facial Images using Local Binary and Non-Binary Descriptors,” Proc. 4th Int. Conf. Comput. Methodol. Commun. ICCMC 2020, no. Iccmc, pp. 631–634, 2020, doi: 10.1109/ICCMC48092.2020.ICCMC-000117.
[9] V. S. Veesam, S. Ravichandran, and R. M. B. Gatram, “Deep Learning-Based Prediction of Age and Gender from Facial Images,” Ing. des Syst. d’Information, vol. 28, no. 4, pp. 1013–1018, 2023, doi: 10.18280/isi.280421.
[10] J. Ma, X. Jiang, A. Fan, J. Jiang, and J. Yan, “Image Matching from Handcrafted to Deep Features: A Survey,” Int. J. Comput. Vis., vol. 129, no. 1, pp. 23–79, 2021, doi: 10.1007/s11263-020-01359-2.
[11] W. Kukuh, R. Ardana, T. Dharmawan, and M. A. Hidayat, “Integration Of Colbp And Viola Jones Feature Extraction Methods In Gender Classification Based On Facial Image,” Int. J. Innov. Enterp. Sysyem, vol. 99, no. 1, pp. 87–100, 2023.
[12] S. Karanwal and M. Diwakar, “OD-LBP: Orthogonal difference-local binary pattern for Face Recognition,” Digit. Signal Process. A Rev. J., vol. 110, p. 102948, 2021, doi: 10.1016/j.dsp.2020.102948.
[13] K. Prasada Rao, M. V. P. Chandra Sekhara Rao, and N. Hemanth Chowdary, “An integrated approach to emotion recognition and gender classification,” J. Vis. Commun. Image Represent., vol. 60, pp. 339–345, 2019, doi: 10.1016/j.jvcir.2019.03.002.
[14] H. Tran, C. Dong, M. Naghedolfeizi, and X. Zeng, “Using cross-examples in viola-jones algorithm for thermal face detection,” Proc. 2021 ACMSE Conf. - ACMSE 2021 Annu. ACM Southeast Conf., pp. 219–223, 2021, doi: 10.1145/3409334.3452083.
[15] F. L. Ramadini and E. Haryatmi, “Penggunaan Metode Haar Cascade Classifier dan LBPH Untuk Pengenalan Wajah Secara Realtime,” InfoTekJar J. Nas. Inform. dan Teknol. Jar., vol. 6, no. 2, pp. 1–8, 2022, [Online]. Available: https://jurnal.uisu.ac.id/index.php/infotekjar/article/view/4714/pdf
[16] C. Rahmad, K. Arai, R. A. Asmara, E. Ekojono, and D. R. H. Putra, “Comparison of Geometric Features and Color Features for Face Recognition,” Int. J. Intell. Eng. Syst., vol. 14, no. 1, pp. 541–551, 2021, doi: 10.22266/IJIES2021.0228.50.
[17] M. Karahan, F. Lacinkaya, K. Erdonmez, E. D. Eminagaoglu, and C. Kasnakoglu, “Face Detection and Facial Feature Extraction with Machine Learning,” Lect. Notes Networks Syst., vol. 308, no. November 2022, pp. 205–213, 2022, doi: 10.1007/978-3-030-85577-2_24.
[18] E. O. Abdulali, A. S. Huwedi, and K. A. Bozed, “Gender detection using random forest,” ACM Int. Conf. Proceeding Ser., 2020, doi: 10.1145/3410352.3410799.
[19] M. Azhari, Z. Situmorang, and R. Rosnelly, “Perbandingan Akurasi, Recall, dan Presisi Klasifikasi pada Algoritma C4.5, Random Forest, SVM dan Naive Bayes,” J. Media Inform. Budidarma, vol. 5, no. 2, p. 640, 2021, doi: 10.30865/mib.v5i2.2937.
[20] R. M. Firzatullah, “Sistem Pendukung Keputusan Penentuan Uang Kuliah Tunggal Universitas XYZ Menggunakan Algoritma Backpropagation,” Petir, vol. 14, no. 2, pp. 170–180, 2021, doi: 10.33322/petir.v14i2.996.