Multi-loss Function in Robust Convolutional Autoencoder for Reconstruction Low-quality Fingerprint Image

Farchan Hakim Raswa, Franki Halberd, Agus Harjoko, Wahyono, Chung Ting Lee, Yung-Hui Li, Jia Ching Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publicationProceedings of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages428-431
Number of pages4
ISBN (Electronic)9786165904773
DOIs
StatePublished - 2022
Event2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022 - Chiang Mai, Thailand
Duration: 7 Nov 202210 Nov 2022

Publication series

NameProceedings of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022

Conference

Conference2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022
Country/TerritoryThailand
CityChiang Mai
Period7/11/2210/11/22

Keywords

  • convolution autoencoder
  • fingerprint
  • loss function
  • reconstruction

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