matlab凹包算法
时间: 2023-08-26 07:17:10 浏览: 385
Matlab中可以使用凸包算法来实现边界搜索。其中一个常见的实现是使用Graham扫描算法来计算凸包。这个算法的基本思路是先找到最下边的点,然后按照极角的大小对其他点进行排序,最后根据排序后的点依次构建凸包。你可以使用Matlab中的convhull函数来实现这个算法。
另外,你提到的边界搜索算法也可以用于搜索盒的边界。该算法的基本思路是从一个初始边界点开始,逐步寻找下一个连接点,直到形成一个闭环。你可以参考引用中给出的边界搜索算法实现代码来实现这个功能。
总的来说,使用凸包算法或者边界搜索算法都可以实现搜索盒的边界。具体使用哪种算法取决于你的需求和数据结构。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* [二维点集凹包算法介绍](https://blog.csdn.net/weixin_39765209/article/details/115880834)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT3_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
- *2* [过滤三角网算法求取凹包(二)](https://blog.csdn.net/dayuhaitang1/article/details/125085411)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT3_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
- *3* [凸包+凹包+凸边凹化算法](https://blog.csdn.net/qingtianhaoshuai/article/details/122245165)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT3_1"}}] [.reference_item style="max-width: 33.333333333333336%"]
[ .reference_list ]
阅读全文
相关推荐
















