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摘要: 提出了独立边界的自增强算法.使用反复随机搜索获得各种可能的独立边界轨迹;使 用搜索轨迹的自增强代替过去的固定点的领域增强方法;采用搜索轨迹的积累技术代替过去的 迭代操作.实验证明:该方法克服了过去的方法对噪声和局部错误极度敏感的缺点,能够在进行 边缘增强的同时有效地抑制噪声.Abstract: We propose the method of self-reinforcement of independent-edges. We use repetitive random searches to obtain various possible independent-edge trajectories, use self-reinforcement of search trajectories to replace reinforcement based on fixed points in relaxation labeling, and use accumulation to replace iteration. Experiments show that our method can solve the problem that the existing methods are very sensitive to noise and local errors, and can reinforce edges well and effectively suppress noise.
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Key words:
- Edge detection /
- edge reinforcement /
- relaxation algorithm /
- random heuristic search /
- accumulation
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