Research on an Improved Segmentation Recognition Algorithm of Overlapping Agaricus bisporus
Abstract
:1. Introduction
- (1)
- We adopt gradient feature to reduce the influence of illumination variance.
- (2)
- Considering grouping the segmented contours as combinatorial optimization, we propose a branch definition algorithm to merge and group the dispersed outlines of the same Agaricus bisporus.
- (3)
- To solve arc segmentation with different curvatures and lengths for reconstruction of Agaricus bisporus contours, we exploit two algorithms: the least square ellipse fitting algorithm for high curvature or long length and the minimum distance circle fitting for low curvature or short length.
2. Segmentation of Overlapping Agaricus bisporus
2.1. Segmentation Based on Image Edge Gradient
2.2. Extraction of Convex and Concave Areas
2.3. Corner Detection and Contour Segmentation
3. Overlapping Agaricus bisporus Outline Grouping
3.1. Problem Description
3.2. Branch Definition Algorithm Grouping
3.3. Grouping Criteria
4. Reconstruction and Recognition of Overlapping Agaricus bisporus
4.1. Least Square Ellipse Fitting Reconstruction Contour
4.2. Minimum Distance Circle Fitting Contour Reconstruction
5. Experiment and Result Analysis
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Method | Number of Samples | Effective Identification Number | Recogniton Reate |
---|---|---|---|
Hough circle transform algorithm | 6109 | 4338 | 71.01% |
Watershed algorithm based on distance transformation | 6109 | 5319 | 87.07% |
The algorithm proposed in this article | 6109 | 6036 | 98.81% |
Methods | Number of Segmentation and Recognition | Number of Successfully Recognited | Average Deviation Rate of Coordinates | Recognition Success Rate | Overall Recognition Success Rate | Average Time (ms) |
---|---|---|---|---|---|---|
Hough circle transform algorithm | 4338 | 3363 | 2.29% | 77.52% | 55.05% | 358 |
Watershed algorithm based on distance transformation | 5319 | 4570 | 1.99% | 85.92% | 74.81% | 224 |
The algorithm proposed in this article | 6036 | 5870 | 1.59% | 97.25% | 96.09% | 212 |
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Yang, S.; Ni, B.; Du, W.; Yu, T. Research on an Improved Segmentation Recognition Algorithm of Overlapping Agaricus bisporus. Sensors 2022, 22, 3946. https://doi.org/10.3390/s22103946
Yang S, Ni B, Du W, Yu T. Research on an Improved Segmentation Recognition Algorithm of Overlapping Agaricus bisporus. Sensors. 2022; 22(10):3946. https://doi.org/10.3390/s22103946
Chicago/Turabian StyleYang, Shuzhen, Bowen Ni, Wanhe Du, and Tao Yu. 2022. "Research on an Improved Segmentation Recognition Algorithm of Overlapping Agaricus bisporus" Sensors 22, no. 10: 3946. https://doi.org/10.3390/s22103946
APA StyleYang, S., Ni, B., Du, W., & Yu, T. (2022). Research on an Improved Segmentation Recognition Algorithm of Overlapping Agaricus bisporus. Sensors, 22(10), 3946. https://doi.org/10.3390/s22103946