python 15 lines · 1 tab

OpenCV image preprocessing for OCR and vision pipelines

Dr. Elena Vasquez Apr 2026

1 tab

import cv2

image = cv2.imread('receipt.jpg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
blurred = cv2.GaussianBlur(gray, (5, 5), 0)
thresholded = cv2.adaptiveThreshold(
    blurred,
    255,
    cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
    cv2.THRESH_BINARY,
    11,
    2,
)

cv2.imwrite('receipt_processed.png', thresholded)

1 file · python Explain with highlit

A lot of computer vision performance comes from cleaner inputs rather than larger models. I use OpenCV for resizing, denoising, thresholding, and contour extraction when preparing images for OCR or downstream classification. These classical steps often save compute and improve stability.

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