Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{143694,
        author = {ankit sonar and Devyani Patil and Manas Tambat and Digvijay Thakare},
        title = {Image Processing for Detecting Sea Ice Floes},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {1},
        pages = {233-236},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=143694},
        abstract = {An unmanned aerial vehicle was used as a mobile sensor platform to collect sea-ice features and several image processing algorithms have been applied to samples of Sea-Ice images to extract useful information about sea-ice. The sea-ice statistics given by the floe size distribution, being an important parameter for climate and wave and structure ice-analysis, is challenging to calculate due to difficulties in ice floe detection, particularly the separation of seemingly connected ice floes. Gray scale and OTSU algorithm will be applied to solve this problem. To evolve the Gray Scale and OTSU algorithm automatically, an initialization based on the distance transform is proposed to detect individual ice floes, and the morphological cleaning is afterward applied to smoothen the shape of each identified ice floe. Based on the identification result, the image is separated into four different layers: ice floes, brash pieces, slush, and water. This makes it further possible to present a color map of the ice floes and brash pieces based on sizes, and the corresponding ice floe size distribution histogram.},
        keywords = {Image Binrization, Image Processing, Image Segmentation},
        month = {},
        }