matlab最小外接矩形法
时间: 2023-10-09 22:09:44 浏览: 126
Matlab中可以使用以下代码实现最小外接矩形法:
1. 首先读入点集数据,可以使用load函数加载txt文件中的数据:
data = load('data.txt');
2. 使用convhull函数计算点集的凸包:
K = convhull(data(:,1), data(:,2));
3. 计算凸包上所有边的斜率:
slope = diff(data(K,2))./diff(data(K,1));
4. 找出斜率最小和最大的两条边,即为最小外接矩形的两个对角线:
[min_slope, min_idx] = min(slope);
[max_slope, max_idx] = max(slope);
5. 计算最小外接矩形的旋转角度:
angle = atan2(max_slope - min_slope, 1 + max_slope * min_slope);
6. 计算最小外接矩形的中心点坐标:
center = mean(data(K([min_idx, max_idx]),:));
7. 计算最小外接矩形的长和宽:
width = norm(data(K(min_idx),:) - data(K(max_idx),:));
height = max(abs(data(K(:,1))*sin(angle) - data(K(:,2))*cos(angle))) * 2;
8. 绘制最小外接矩形:
rectangle('Position', [center(1)-width/2, center(2)-height/2, width, height], 'EdgeColor', 'r');
完整代码如下:
data = load('data.txt');
K = convhull(data(:,1), data(:,2));
slope = diff(data(K,2))./diff(data(K,1));
[min_slope, min_idx] = min(slope);
[max_slope, max_idx] = max(slope);
angle = atan2(max_slope - min_slope, 1 + max_slope * min_slope);
center = mean(data(K([min_idx, max_idx]),:));
width = norm(data(K(min_idx),:) - data(K(max_idx),:));
height = max(abs(data(K(:,1))*sin(angle) - data(K(:,2))*cos(angle))) * 2;
rectangle('Position', [center(1)-width/2, center(2)-height/2, width, height], 'EdgeColor', 'r');
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