IMPLEMENTASI FILTER SKETSA CITRA DIGITAL MELALUI OPERASI KONVOLUSI DENGAN MATRIK KERNEL LAPLACE OF GAUSS
Abstract
Sketch filter is used usually as a preliminary process of the images due to further processing such as in pattern recognition of a certain object by deep learning method. Several types of sketch filter can be used to detect the edge of object. In this paper the implementation of convolution operation by the Laplace of Gauss kernel matrix is explored to be used as a sketch filter to detect the edge of object.
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References
Asghari, M.H. & Jalali, B. 2015. “Edge Detection in Digital Images using Dispersive Phase Stretch Transform”. International Journal of Biomedical Imaging, Vol-15, Id 687819. Doi: 10.1155/2015/687819
Chang, Q., Li, X., Li, Y. & Miyazaki, J. 2023. “Multi-directional Sobel operator kernel on GPUs”. Journal of Parallel and Distributed Computing. Preprint
Farooq, M.S., Arif, T. & Riaz, S. 2023. “Detection of Late Blight Disease in Tomato leaf Using Image Processing Techniques”. https://arxiv.org/pdf/2306.06080.pdf
Galea, C. and Farrugia, R.A. 2016. “Face Photo-Sketch Recognition using Local and Global Texture Descriptors”. 24th European Signal Processing Conference. Doi: 10.1109/ eusipco.2016.7760647
Gulo, H. (2020). Penerapan Laplacian of Gaussian Dalam Mendeteksi Tepi Luka Bakar Pada Manusia. TIN: Terapan Informatika Nusantara, 1(7), 339–349.
Jiang, B. and Liu, S. 2013. “Expressive Image Sketching with Two-Layer Image Features”, Seventh International Conference on Image and Graphics, Doi: 10.1100/icig.2013.187
Khayan, A. and Khoenkaw, P. 2021. “Automatic Pencil Sketch Landscape Image Generation from Photograph”, Sixth International Conference on Digital Arts, Media and Technology
Klum, S., Han, H., Jain, A.K. and Klare, B. 2013. “Sketch based Face Recognition: Forensic vs. Composite Sketches”, International Conference on Biometrics. Doi: 10.1109/icb. 2013.6612993
Lin, X., Zhou, Y., Liu, Y. & Zhu, C. 2023. “Level-Line Guided Edge Drawing for Robust Line Segment Detection”. https://arxiv.org/pdf/2305.05883.pdf
Lu, J., Zhang, Z. and Chen, H. 2022. “A Two-Layer Sketch for Entropy Estimation in Data Plane”, Seventh International Conference on Cloud Computing and Big Data Analytics, Doi: 10.1109/icccbda55098.2022.9778903
Marpaung, F., Aulia, F., & Nabila, R. C. (2022). COMPUTER VISION DAN PENGOLAHAN CITRA DIGITAL. PUSTAKA AKSARA.
Peng, C., Gao, X., Wang, N., Tao, D, Li, X. and Li, J. 2015. “Multiple representations-based Face Sketch-Photo Synthesis”, IEEE Transactions on Neural Networks and Learning Systems, vol.27(11), 2201-2215, doi:10.1109/tnnls.2015. 2464681
Prasetyo, E. D. (2020). Deteksi Tepi Menggunakan Metode Laplacian of Gaussian Pada Citra Bola Futsal. TIN: Terapan Informatika Nusantara, 1(6), 309–316.
Purwandari, E. P., Vatresia, A., & Siburian, S. (2019). Deteksi Image Splicing Pada Citra dengan Metode Discrete Cosine Transform (DCT) dan Scale Invariant Feature Transform (SIFT). Pseudocode, 6(2), 138–148.
Setyawan, G. C., & Nawansari, M. P. (2022). Kinerja Penapisan Gaussian dan Median Dalam Pelembutan Citra. Journal of Information Technology, 2(2), 1–4.
Seo, J., Wagner, J., Raicura, A. & Kim, J. 2023. “Vision and Control for Grasping Clear Plastic Bags”. https://arxiv.org/pdf/2305.07631.pdf
Sinurat, S., & Siagian, E. R. (2021). Peningkatan Kualitas Citra Dengan Gaussian Filter Terhadap Citra Hasil Deteksi Robert. Pelita Informatika: Informasi Dan Informatika, 9(3), 225–231.
Stephane, M., Charlotte, P. 2015. “Primal Sketch of Image Series with Edge Preserving Filtering Application to Change Detection”, Eight International Workshop on the Analysis of Multitemporal Remote Sensing Images. Doi: 10.1109/multi.temp.2015. 7245785
Wan, W., and Lee, H.J. 2017. “Face Sketch Synthesis with Joint Training Model”, International Conference on Computer Theory and Applications. Doi: 10.1109/iccta43079.2017.94972
Xu, X., Wang, R. & Lu, J. 2023. “Low-Light Image Enhancement via Structure Modeling and Guidance”. https://arxiv.org/pdf/2305.05839.pdf
Yusuf, F. (2017). Pendeteksian Nomor Polisi Kendaraan Bermotor Berbasis Citra Digital Menggunakan Metode Binerisasi Dan Tempale Matching. Teknosains: Media Informasi Sains Dan Teknologi, 11(1).
Zangpo, P., Kawabe, T. & Kobayashi, H. 2023. “Edge-Enhanced Microscopy of Complex Object using Scalar and Vectorial Vortex Filtering”. https://arxiv.org/pdf/2305.07225.pdf
Zhang, X., Li, X., Ouyang, S. and Liu, Y. 2017. “Photo-to-Sketch Transformation in a Complex background”, IEEE Access, 5, 8727-8735
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