ACADSTAFF UGM
| Title | : | Multi-loss Function in Robust Convolutional Autoencoder for Reconstruction Low-quality Fingerprint Image |
| Author | : |
FARCHAN HAKIM RASWA (1) FRANKI HALBERD (2) Prof. Drs. Agus Harjoko, M.Sc., Ph.D. (3) Wahyono, Ph.D. (4) Chung-Ting Lee (5) Yung-Hui Li (6) Jia Ching Wang (7) |
| Date | : | 7 2022 |
| Keyword | : | loss function,reconstruction,fingerprint,convolution autoencoder loss function,reconstruction,fingerprint,convolution autoencoder |
| Abstract | : | Our research is fingerprint reconstruction based on a convolutional autoencoder. We combine the perceptual measurement as a multi-loss function to give satisfactory weight correction, such as the structural similarity index measure (SSIM), Mean Absolute Error (MAE), and peak signal-to-noise ratio (PSNR). We observed and investigated the result using multi-loss functions and other loss functions. Eventually, our experiment obtained the highest image quality metric scores from the experimental result summarized as a loss function (SSIM + PSNR) with optimizer Root Mean Squared Propagation (RMSprop). We evaluated the image reconstruction using a dataset from FVC2004. Eventually, our proposed method gets impressive results, increasing the image's average quality by PSNR of 20.58%, SSIM of 4.07%, and MSE of 38.92%, respectively. |
| Group of Knowledge | : | |
| Level | : | Internasional |
| Status | : |
Published
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