Underwater Images of Stony Reefs in Turbid Temperate Waters: A Dataset for Evaluating Textural Descriptors

The data presented here were collected from 33 sampling sites in the coastal and offshore reefs of the southeastern Baltic Sea (depths ranging from 4.4 to 42.2 m) during the summer-autumn sampling seasons of 2022–2023. This dataset includes 124 video frames (divided into training and testing), 2,800 patches (100x100 px), with 350 patches for each class, along with annotated data. Five key biological classes representing different textures were selected: red algae Furcellaria lumbricalis, brown algae Vertebrata fucoides, green algae Cladophora sp., and large and small blue mussels (M. edulis trossulus). Additionally, three lithological classes were chosen: stable substrates consisting of cobbles (6–25 cm) and boulders (>25 cm), pebbles (0.2–6 cm), and sand (<0.2 cm). The testing dataset was used to create annotated data, which include pixel-wise segmentation of 165 images, annotated by three benthic experts. The extracted patches from the frames can be used for image classification based on textural descriptors, while the annotations can be used to validate the classification results.

本数据集收录了2022-2023年夏季至秋季期间，于东南波罗的海沿岸及近海礁石（深度介于4.4至42.2米之间）的33个采样点收集的数据。该数据集包含124帧视频（分为训练集和测试集）、2,800个图像块（100x100像素），每个类别包含350个图像块，以及标注数据。选取了代表不同质地的五种关键生物类别：红藻（Furcellaria lumbricalis）、褐藻（Vertebrata fucoides）、绿藻（Cladophora sp.）以及大、小贻贝（M. edulis trossulus）。此外，还选择了三种岩性类别：由砾石（6-25厘米）和巨砾（>25厘米）构成的稳定基座、卵石（0.2-6厘米）以及沙粒（<0.2厘米）。测试数据集被用于创建标注数据，包括165张图像的像素级分割，由三位底栖生态专家进行标注。从帧中提取的图像块可用于基于纹理描述符的图像分类，而标注数据则可用于验证分类结果。

搜集汇总

背景与挑战

背景概述

该数据集是一个用于评估纹理描述符的水下图像集合，采集自波罗的海东南部浑浊温带水域的33个采样点，覆盖2022-2023年夏秋季，深度范围4.4至42.2米。它包含124个视频帧、2,800个补丁和带专家标注的像素级分割数据，涵盖红藻、褐藻、绿藻、蓝贻贝等生物类别以及稳定基质、卵石、沙子等岩性类别，适用于图像分类和生态纹理分析。