Apply Threshold

Apply a threshold to an image to create a binary (black and white) image.

Request Parameters

Response

Returns the thresholded binary image in the same format as the input file.

Example Request

    curl -X POST "https://oyyi.xyz/api/image/threshold"   -H "accept: application/json" \
  -H "Content-Type: multipart/form-data" \
  -F "file=@image.jpg" \
  -F "threshold_value=128" \
  --output threshold.jpg
  

Example with Python

    import requests

url = "https://oyyi.xyz/api/image/threshold"

files = {
    'file': open('image.jpg', 'rb')
}

data = {
    'threshold_value': 128
}

response = requests.post(url, files=files, data=data)

# Save the thresholded image
with open('threshold.jpg', 'wb') as f:
    f.write(response.content)
  

Example with JavaScript

    // Using fetch API
const formData = new FormData();
formData.append('file', fileInput.files[0]);
formData.append('threshold_value', '128');

fetch('https://oyyi.xyz/api/image/threshold', {
  method: 'POST',
  body: formData
})
.then(response => response.blob())
.then(blob => {
  // Create a URL for the blob
  const url = URL.createObjectURL(blob);

  // Create a link to download the image
  const a = document.createElement('a');
  a.href = url;
  a.download = 'threshold.jpg';
  a.click();

  // Clean up by revoking the URL
  URL.revokeObjectURL(url);
})
.catch(error => console.error('Error:', error));
  

Thresholding Methods

How It Works

Thresholding converts a grayscale image to a binary (black and white) image by setting each pixel to either black or white based on its intensity compared to a threshold value:

• Simple method: Uses a single global threshold value for the entire image.
• Adaptive method: Calculates different threshold values for different regions of the image based on local statistics. This is controlled by the block_size (size of the local region) and c (adjustment constant) parameters.
• Otsu method: Automatically calculates the optimal threshold value by analyzing the image histogram to minimize the variance between black and white pixels.

Threshold Value Examples

Error Responses

Notes

• For the simple method, a threshold value of 128 is a good starting point for most images.
• Lower threshold values will result in more white pixels, higher values in more black pixels.
• The adaptive method is better for images with uneven lighting or shadows.
• The Otsu method automatically calculates the optimal threshold and ignores the threshold_value parameter.
• The maximum file size allowed is 10MB.
• The image is converted to grayscale before thresholding if it's not already grayscale.
• For adaptive thresholding, the block_size must be an odd number. Larger values result in more global thresholding, smaller values in more local adaptation.

Use Cases

• Document scanning and text extraction
• Creating silhouettes or cutouts
• Simplifying complex images for analysis
• Creating high-contrast artistic effects
• Preparing images for edge detection or contour finding
• Isolating objects from backgrounds
• Barcode or QR code reading
• Medical image analysis