KU-BD-Fish: High-Resolution White-Background and Segmented Images for Species Classification

This dataset comprises 940 high‑resolution images of 26 freshwater fish species native to Bangladesh. In order to ensure all procedure are performed on a uniform standard and scientific basis, each specimen was photographed individually against white background with controlled lighting using an iPhone 14 Plus and Samsung S23 Plus.
The dataset contains two versions of every image: the original unprocessed photograph with the white background and a segmented version where the background has been removed to isolate the fish.

Acquisition equipment: iPhone 14 Plus and Samsung S23 Plus smartphones.

Image formats:
1.Raw images: Original photographs with a consistent white background.
2.Segmented images: Background removed to highlight each fish specimen.

Representation of species: 26 different species of freshwater fish from Bangladesh, each with several photos.
File organisation: The images are organised into folders that are specific to each species, and a metadata file that goes with them provides a list of the species names and other pertinent information.For example the folder named Rui contains all the photos of Rui fish in both Raw_images and Segmented_Images folder.

The following are some possible uses for these datasets:

1. Morphological analysis: It is useful for accurately measuring and comparing the body structures of fish.
2. Machine-learning research: It can be used to train and assess models for segmentation, object detection, and species classification.
3. Educational use: It offers excellent specimen photos for conservation education, aquaria, and ichthyology classes.
4. Taxonomic and biodiversity research: Its standardized, high-resolution specimen images can facilitate accurate species identification and reliable assessments of biodiversity, supporting ecological and conservation research.