用halcon 写一个3d 轮廓匹配算法
时间: 2024-05-02 21:20:20 浏览: 13
以下是一个简单的3D轮廓匹配算法示例,使用Halcon实现:
1. 读取模板和目标点云数据
```python
read_object_model_3d('template.ply', 'template', [], [], GenParamName, GenParamValue)
read_object_model_3d('target.ply', 'target', [], [], GenParamName, GenParamValue)
```
2. 提取模板和目标点云的表面
```python
surface_normals_object_model_3d('template', 0.01, [], [], Normals)
surface_normals_object_model_3d('target', 0.01, [], [], Normals)
```
3. 对表面进行采样
```python
sample_object_model_3d('template', 'voxel', 0.1, [], [], SampledObjectModel)
sample_object_model_3d('target', 'voxel', 0.1, [], [], SampledObjectModel)
```
4. 提取模板和目标点云的特征
```python
features_object_model_3d('template', 'fpfh', [], [], Features)
features_object_model_3d('target', 'fpfh', [], [], Features)
```
5. 进行特征匹配
```python
match_feature_model_3d('target', 'fpfh', 'template', 'fpfh', [], [], [0.9], [Match], [Score])
```
6. 计算变换矩阵
```python
hom_mat3d_from_match_model_3d('template', 'target', 'fpfh', 'fpfh', Match, [], [], HomMat3D)
```
7. 通过变换矩阵将模板点云变换到目标点云坐标系中
```python
transform_object_model_3d('template', HomMat3D, [], [], TransformedObjectModel)
```
8. 评估匹配结果
```python
evaluate_feature_matching_result_model_3d('template', 'target', 'fpfh', 'fpfh', Match, [], [], [], [], EvaluatedResult)
```