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Image Roberts Cross Edge Detection

Apply Roberts Cross operator for simple and fast edge detection, particularly effective for diagonal edges

Click to upload file or drag and drop file here

Maximum file size: 10MB Supported formats: image/jpeg, image/png, image/webp, image/gif, image/bmp, image/tiff

Image to apply Roberts Cross edge detection

Direction of diagonal edge detection to apply

Threshold for edge detection (0-255). Higher values detect only strong edges

How to render the edge detection results

Normalize the output to enhance edge visibility

Key Facts

Category
Design
Input Types
file, select, number, checkbox
Output Type
file
Sample Coverage
4
API Ready
Yes

Overview

The Image Roberts Cross Edge Detection tool provides a fast and efficient way to identify edges in images by calculating the spatial gradient. It is particularly effective at highlighting diagonal features, making it a lightweight solution for image processing tasks that require quick structural analysis.

When to Use

  • •When you need to perform rapid, low-latency edge detection on images.
  • •When your image contains significant diagonal structures that require precise highlighting.
  • •When you need a simple gradient-based approach to isolate object boundaries.

How It Works

  • •Upload your image file in a supported format like JPEG, PNG, or TIFF.
  • •Select the detection direction, such as main diagonal, anti-diagonal, or both.
  • •Adjust the threshold and output mode to refine the visibility of the detected edges.
  • •Apply the transformation to generate a processed image highlighting the identified edges.

Use Cases

Extracting structural outlines from technical drawings or diagrams.
Preprocessing images for computer vision tasks where diagonal alignment is critical.
Quickly identifying high-contrast boundaries in simple grayscale images.

Examples

1. Highlighting Diagonal Structural Lines

Graphic Designer
Background
A designer needs to extract the geometric skeleton of a minimalist architectural sketch to use as a vector guide.
Problem
The original image has soft lines that are difficult to trace manually.
How to Use
Upload the sketch, set the detection direction to 'Both Diagonals', and choose 'Binary Edges' for a clean, high-contrast output.
Example Config
direction: both, outputMode: binary, normalize: true
Outcome
A sharp, binary image showing only the primary diagonal edges, ready for vector conversion.

2. Rapid Edge Analysis for Quality Control

Quality Assurance Engineer
Background
An engineer needs to verify the alignment of diagonal components on a manufactured part using a standard camera feed.
Problem
Standard edge detection is too slow for the real-time inspection workflow.
How to Use
Upload the component image, set a threshold of 50 to ignore background noise, and use 'Grayscale Edges' to visualize the gradient intensity.
Example Config
threshold: 50, outputMode: grayscale, normalize: true
Outcome
A clear grayscale map of the component's edges, allowing for immediate visual verification of alignment.

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FAQ

What is the Roberts Cross operator?

It is a simple 2x2 convolution kernel used in image processing to compute the gradient magnitude, which helps in detecting edges.

Is this tool suitable for complex edge detection?

It is best for simple, fast detection. For more complex or noise-heavy images, you might require more advanced algorithms.

What image formats are supported?

The tool supports common formats including JPEG, PNG, WebP, GIF, BMP, and TIFF.

How does the threshold setting affect the output?

The threshold filters out weak gradients; higher values ensure that only the most prominent edges are displayed in the final output.

Can I invert the edge colors?

Yes, you can select the 'Negative Edges' output mode to invert the colors of the detected edges.

API Documentation

Request Endpoint

POST /en/api/tools/image-roberts

Request Parameters

Parameter Name Type Required Description
imageFile file (Upload required) Yes Image to apply Roberts Cross edge detection
direction select No Direction of diagonal edge detection to apply
threshold number No Threshold for edge detection (0-255). Higher values detect only strong edges
outputMode select No How to render the edge detection results
normalize checkbox No Normalize the output to enhance edge visibility

File type parameters need to be uploaded first via POST /upload/image-roberts to get filePath, then pass filePath to the corresponding file field.

Response Format

{
  "filePath": "/public/processing/randomid.ext",
  "fileName": "output.ext",
  "contentType": "application/octet-stream",
  "size": 1024,
  "metadata": {
    "key": "value"
  },
  "error": "Error message (optional)",
  "message": "Notification message (optional)"
}
File: File

AI MCP Documentation

Add this tool to your MCP server configuration: 

{
  "mcpServers": {
    "elysiatools-image-roberts": {
      "name": "image-roberts",
      "description": "Apply Roberts Cross operator for simple and fast edge detection, particularly effective for diagonal edges",
      "baseUrl": "https://elysiatools.com/mcp/sse?toolId=image-roberts",
      "command": "",
      "args": [],
      "env": {},
      "isActive": true,
      "type": "sse"
    }
  }
}

You can chain multiple tools, e.g.: `https://elysiatools.com/mcp/sse?toolId=png-to-webp,jpg-to-webp,gif-to-webp`, max 20 tools.

Supports URL file links or Base64 encoding for file parameters.

If you encounter any issues, please contact us at [email protected]