CoralSCOP-LAT: Labeling and Analyzing Tool for Coral Reef Images with Dense Mask

• URL: http://arxiv.org/abs/2410.20436v2
• Date: Mon, 06 Oct 2025 09:41:21 GMT
• Title: CoralSCOP-LAT: Labeling and Analyzing Tool for Coral Reef Images with Dense Mask
• Authors: Yuk-Kwan Wong, Ziqiang Zheng, Mingzhe Zhang, David Suggett, Sai-Kit Yeung,
• Abstract summary: CoralSCOP-LAT is a coral reef image analysis and labeling tool that automatically segments and analyzes coral regions.<n>Our evaluations demonstrate that CoralSCOP-LAT surpasses existing coral reef analysis tools in terms of time efficiency, accuracy, precision, and flexibility.
• Score: 20.267378309290116
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Coral reef imagery offers critical data for monitoring ecosystem health, in particular as the ease of image datasets continues to rapidly expand. Whilst semi-automated analytical platforms for reef imagery are becoming more available, the dominant approaches face fundamental limitations. To address these challenges, we propose CoralSCOP-LAT, a coral reef image analysis and labeling tool that automatically segments and analyzes coral regions. By leveraging advanced machine learning models tailored for coral reef segmentation, CoralSCOP-LAT enables users to generate dense segmentation masks with minimal manual effort, significantly enhancing both the labeling efficiency and precision of coral reef analysis. Our extensive evaluations demonstrate that CoralSCOP-LAT surpasses existing coral reef analysis tools in terms of time efficiency, accuracy, precision, and flexibility. CoralSCOP-LAT, therefore, not only accelerates the coral reef annotation process but also assists users in obtaining high-quality coral reef segmentation and analysis outcomes. Github Page: https://github.com/ykwongaq/CoralSCOP-LAT.

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