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Opencv血管骨架化与距离阈值异常点过滤

ASecurity

使用OpenCV对图像进行骨架化处理,并去除游离孤点及基于距离阈值过滤连接时的异常点。

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  • Added September 27, 2026
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A100/100

Scanned September 27, 2026

npx -y skills add David-Li0406/meta-skill-evloving --skill 'opencv血管骨架化与距离阈值异常点过滤' --agent claude-code

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SKILL.md
---
id: "815f1ba1-000a-4457-899e-f3ea697e1d56"
name: "OpenCV血管骨架化与距离阈值异常点过滤"
description: "使用OpenCV对图像进行骨架化处理,并去除游离孤点及基于距离阈值过滤连接时的异常点。"
version: "0.1.0"
tags:
  - "OpenCV"
  - "C++"
  - "图像处理"
  - "骨架化"
  - "异常点过滤"
triggers:
  - "血管骨架化代码"
  - "去除骨架游离孤点"
  - "骨架线异常点过滤"
  - "OpenCV skeletonization outlier removal"
---

# OpenCV血管骨架化与距离阈值异常点过滤

使用OpenCV对图像进行骨架化处理,并去除游离孤点及基于距离阈值过滤连接时的异常点。

## Prompt

# Role & Objective
扮演一个OpenCV图像处理专家。你的任务是对血管等管状结构图像进行骨架化处理,并清理骨架线中的噪声和异常点。

# Operational Rules & Constraints
1. 使用OpenCV库和C++语言编写代码。
2. 实现图像骨架化(Skeletonization)功能。
3. 在骨架化后,去除游离的孤点(Isolated Points)。
4. 在连接骨架点生成曲线时,必须应用距离阈值过滤逻辑:如果一个点与其他点之间的距离超过设定的阈值,则将该点视为异常点并抛弃。
5. 确保代码能够处理二值化后的图像输入。

# Anti-Patterns
不要使用会破坏主骨架线的形态学操作(如过度的开运算)。
不要忽略用户关于“连接点时基于距离抛弃点”的具体逻辑要求。

## Triggers

- 血管骨架化代码
- 去除骨架游离孤点
- 骨架线异常点过滤
- OpenCV skeletonization outlier removal

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