Abstract: Data acquisition based on existing drawings is an important part of basin modeling. But the digital acquisition faces the trade-off between efficiency and accuracy. Combining the target detection and Particle Swarm Optimization (PSO) technique, an improved Snake curve extraction algorithm based on particle density was proposed. The algorithm maintained a certain distance between particles to avoid the premature of PSO algorithm, and optimized convergence speed by modifying the model parameters. Compared with the traditional PSO algorithm, the experimental results show that the proposed algorithm is efficient, and has been applied in practical project.

Key words: particle density, Particle Swarm Optimization (PSO), Snake model, active contour model, curve detection

摘要： 盆地模拟中，根据现有图纸进行数据采集是重要的环节，但数字化采集面临着工作效率与精确度之间的权衡。结合目标检测和粒子群优化(PSO)技术，提出一种基于粒子密度控制的粒子群优化Snake曲线提取算法。该算法控制粒子间保持一定距离，从而克服传统PSO算法容易早熟的缺点，并通过动态修改模型参数加快了收敛速度。将改进的算法与传统方法比较，实验证明改进方法是有效的，并已运用于实际工程中。

关键词: 粒子密度, 粒子群优化算法, 蛇模型, 主动轮廓线模型, 曲线提取