Analysis of Effect of Image Augmentation with Image Enhancement on Fish Image Classification Using Convolutional Neural Network

Daffa Muhamad Azhar*, Nanik Suciati, Chastine Fatichah

*Corresponding author for this work

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

Abstract

Developing a fish species classification model using a Convolutional Neural Network (CNN) requires a diverse and abundant training dataset. In addition, the quality of the images in the dataset also affects the model's performance. This research aims to investigate the effect of image enhancement through augmentation on fish image classification using CNN. The Fish-gres dataset is used in this study, and two image enhancement techniques, Histogram Equalization (HE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) are applied to the training dataset. The experiment involved a non-pre-trained CNN and three pre-trained CNN models (ResNet50, Xception, and VGG16) trained using three different datasets, i.e., the original training data, training data augmented with HE, and training data augmented with CLAHE. We also experimented using different learning rates. The accuracies of each model are compared and evaluated. The experiment results showed that all models except Xception augmented with HE and CLAHE produced higher accuracy performance than those without augmentation. The best model for the Fish-gres dataset is CNN with ResNet50 pre-trained model, HE-augmented training data, and a learning rate of 10^-3 with 100% accuracy.

Original languageEnglish
Title of host publication2023 14th International Conference on Information and Communication Technology and System, ICTS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages129-134
Number of pages6
ISBN (Electronic)9798350312164
DOIs
Publication statusPublished - 2023
Event14th International Conference on Information and Communication Technology and System, ICTS 2023 - Surabaya, Indonesia
Duration: 4 Oct 20235 Oct 2023

Publication series

Name2023 14th International Conference on Information and Communication Technology and System, ICTS 2023

Conference

Conference14th International Conference on Information and Communication Technology and System, ICTS 2023
Country/TerritoryIndonesia
CitySurabaya
Period4/10/235/10/23

Keywords

  • CLAHE
  • CNN
  • Fish Image Classification
  • HE
  • Image Augmentation

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