ArticleScientific reports2022
A method of blasted rock image segmentation based on improved watershed algorithm.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 78 citations in OpenAlex.
- LDLK-U-Mamba: An Efficient and Highly Accurate Method for 3D Rock Pore Segmentation.Sensors (Basel, Switzerland) · 2025Article
- An End-to-End Particle Gradation Detection Method for Earth-Rockfill Dams from Images Using an Enhanced YOLOv8-Seg Model.Sensors (Basel, Switzerland) · 2025Article
- Multi-resolution X-ray micro-computed tomography images of carbonate rocks from brazilian pre-salt.Scientific data · 2024Article
- Application of improved and efficient image repair algorithm in rock damage experimental research.Scientific reports · 2024Article
- Review of Image-Processing-Based Technology for Structural Health Monitoring of Civil Infrastructures.Journal of imaging · 2024Review
- A rapid evaluation method of blasting effect based on optimized image segmentation algorithm and application in engineering.Scientific reports · 2024Article
- Research on anti-clogging of ore conveyor belt with static image based on improved Fast-SCNN and U-Net.Scientific reports · 2023Article
- Discrete Geodesic Distribution-Based Graph Kernel for 3D Point Clouds.Sensors (Basel, Switzerland) · 2023Article
- DTLR-CS: Deep tensor low rank channel cross fusion neural network for reproductive cell segmentation.PloS one · 2023Article
- Optimizing Multiple Entropy Thresholding by the Chaotic Combination Strategy Sparrow Search Algorithm for Aggregate Image Segmentation.Entropy (Basel, Switzerland) · 2022Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
It is of great theoretical significance and practical value to establish a fast and accurate detection method for particle size of rock fragmentation. This study introduces the Phansalkar binarization method, proposes the watershed seed point marking method based on the solidity of rock block contour, and forms an adaptive watershed segmentation algorithm for blasted rock piles images based on rock block shape, which is to better solve the problem of incorrect segmentation caused by adhesion, stacking and blurred edges in blasted rock images. The algorithm first obtains the binary image after image pre-processing and performs distance transformation; then by selecting the appropriate gray threshold, the adherent part of the distance transformation image, i.e., the adherent rock blocks in the blasted rock image, is segmented and the seed points are marked based on the solidity of the contour calculated by contour detection; finally, the watershed algorithm is used to segment. The area cumulative distribution curve of the segmentation result is highly consistent with the manual segmentation, and the segmentation accuracy was above 95.65% for both limestone and granite for rock blocks with area over 100 cm
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