원문정보
초록
영어
From the perspective of the two-dimensional image processing threshold departure, combining the fuzzy theory and two-dimensional entropy algorithm, collecting and processing trees image contained calibration information point, to determine the optimum threshold value, achieve precise image information extraction point of trees. During the experiment,will be gathering information points marked red rectangle on the image of the trees, and the use of binocular vision platform for the collection, then using the membership based on fuzzy theory merge trees image smoothing, the principle of maximum degree of membership criteria for the selection of the pixel template, optimized calibration point boundary and details, combined with the two-dimensional entropy algorithm to determine the optimal threshold, realize precise point of the image information extraction. The results show that the information point for calibration, image processing method adopted fuzzy theory and two-dimensional entropy algorithm combining, extracting information points is more accurate, clear, can better reflect the characteristics of the image information points, and can achieve the wireless remote monitoring studies of trees, and promote the rapid development of information technology forestry laid a good technical and theoretical foundation.
목차
1. Introduction
2. Theoretical Basis
2.1. Fuzzy Membership Theory
2.2. Two-dimensional Entropy Theory
3. Experiment Design
4. Results and Analysis
5. Conclusion
References