To enhance Tesseract OCR's image detection capabilities, you can focus on preprocessing the images to improve their quality and clarity. Here are some tips:
Resolution and DPI: Ensure the image has a resolution of at least 300 DPI. Tesseract performs best when the height of capital letters is around 30-33 pixels.
Binarization: Convert the image to black and white to reduce noise and improve text contrast.
Deskewing and Dewarping: Correct any skewed or distorted text lines to make them horizontal and straight.
Noise Reduction: Use filters like Gaussian blur or median blur to smooth out noise and irregularities.
Contrast Enhancement: Increase the contrast of the image to make the text stand out more clearly.
Cropping: Remove unnecessary parts of the image to focus on the text area.
Segmentation Mode (PSM): Choose the appropriate Page Segmentation Mode (PSM) in Tesseract based on the layout of your text (e.g., single block of text, sparse text, etc.).
Language Training: If you're working with a specific language or font, train Tesseract with custom data for better accuracy.
Use Tools: Tools like OpenCV or ImageMagick can help automate preprocessing tasks.
