This interface provide functionalities of blob analysis. 该接口提供斑点分析的功能。 Blob analysis is a useful approach to segment object from background into connected components of similar grayscale values. 斑点分析是机器视觉系统中常见的前景目标分割方法，用于从背景中提取灰度值近似的连通域生成斑点对象。 Various geometric features, such as area, perimeter o...
AI agents invoke il_blob_analysis_color to trigger actions in Leaper Vision Toolkit. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
imageUrl | string | — | 图片的url地址，通过这个地址获取到图片 |
paramsInfo | string | — | 工具的参数配置，传入一个序列化的json字符串，属性包括：AddBlobFilter（过滤器）、AddBlobRangeColor（斑点对象的彩色值范围)AddBlobFilter 有一个属性：SetFilterFeature，过滤条件在这里设置，值为一个对象。SetFilterFeature 对象的键为 LPVBlo |
RoiILRegion | string | — | 指定的Roi区域。如果用户没有指定区域，请直接传入 "null"。 如果用户指定区域，传入一个序列化的JSON字符串，属性包括：LpvClassName(调用工具函数的名称) 和 InputParameterFile(调用工具函数需要传入的参数文件名称)。这两个属性的值可以从前处理的MCP工具的返回值中获取。LpvCl |
Parameters from the server's own tool schema.
Blob analysis involves executing image processing algorithms (segmentation, binarization, feature extraction) on input images and producing derived outputs (masks, geometric measurements). This goes beyond passive data retrieval — it runs a computational pipeline. Classified as Execute due to triggering external image processing operations whose effects depend on the input image and configuration parameters.
From the tool's definition 'This interface provide functionalities of blob analysis' — performs image segmentation, connected component analysis, geometric feature computation, and returns serialized JSON with binarized mask image and blob analysis results.
Attacks that exploit this kind of access
This interface provide functionalities of blob analysis. 该接口提供斑点分析的功能。 Blob analysis is a useful approach to segment object from background into connected components of similar grayscale values. 斑点分析是机器视觉系统中常见的前景目标分割方法，用于从背景中提取灰度值近似的连通域生成斑点对象。 Various geometric features, such as area, perimeter or circularity, can be computed on these blobs. 再计算斑点对象的属性特征，典型的几何特征如面积、轮廓周长、圆度等，图像特征如平均亮度、对比度等。 This is a color-mode blob analysis tool. 这个是彩色斑点分析工具。 返回结构是一个序列化的json，其中Preview属性是输入图像在当前斑点分析配置下的二值化蒙版的图片地址， Build 为斑点分析结果，其中的Count表示斑点的数量，Item是所有斑点的集合， 每一个斑点的: GetCenter 表示斑点的重心坐标; CountContour 表示斑点的外轮廓个数； CountHole 表示斑点的孔洞个数； GetRect 表示斑点的包围矩形； GetRotRect 表示斑点的包围旋转矩形； GetFeature是斑点的其他属性，包括：LPVBlobArea表示斑点面积、LPVBlobCenterX和LPVBlobCenterY表示斑点中心点的坐标; ToRegion 表示根据该斑点的轮廓蒙版，生成一个蒙版区域对象； LpvClassName 表示调用工具函数的名称； InputParameterFile 表示调用工具函数需要传入的参数文件名称. It is categorised as a Execute tool in the Leaper Vision Toolkit MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
il_blob_analysis_color accepts 3 parameters: imageUrl, paramsInfo, RoiILRegion. The full parameter table on this page comes from the server's own tool schema.
Register the Leaper Vision Toolkit MCP server in PolicyLayer and add a rule for il_blob_analysis_color: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Leaper Vision Toolkit. Nothing to install.
il_blob_analysis_color is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the il_blob_analysis_color rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for il_blob_analysis_color. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
il_blob_analysis_color is provided by the Leaper Vision Toolkit MCP server (leaper-mcp/leaper-mcp-proxy). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
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