Added ability to perform image preprocessing. This would perform grayscale conversion, denoising and binarization. This should help improve OCR accuracy.

Author: raaj-akshar

image_preprocessing.py

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+"""
+Responsible for doing image preprocessing. Image preprocessing is need to make the image clearer, crispier and easier to read.
+
+OCR performs better if the image is:
+    - grayscale
+    - denoised
+    - binarised
+
+grayscale conversion: Convert from RGB space to grayscale space. Thus converting a color image into a black-and-white image. Each pixel represents intensity rather than color. Reduces complexity from 3 color channels to 1.
+denoised: Applies filters and removes dots, specks and blurs. Currently MedianBlur algorithm is being used with Pillow.
+binarised: Convert grayscale image to binary. Removed background clutter. Each pixel becomes either black(0) or white(255). Dark becomes darker and light becomes lighter.
+
+TODO:
+- DPI Normalization: to make the image crispier and easy to read
+- Contour detection
+
+Currently we are using Pillow, which is basic. We can move to opencv which has better denoising and binarization support. Also it supports contour detection and DPI normalization.
+"""
+
+import os
+import logging
+from PIL import Image, ImageFilter
+
+logger = logging.getLogger(__name__)
+
+
+def preprocess_image(file_path: str):
+    try:
+        base, ext = os.path.splitext(file_path)
+        ext = ext.lstrip(".")
+        im = Image.open(file_path)
+        image_grayscale = im.convert("L")
+        image_denoised = image_grayscale.filter(ImageFilter.MedianFilter(size=3))
+        image_binary = image_denoised.point(lambda x: 0 if x < 128 else 255, mode='1')
+        output_path = f"{base}-processed.{ext}"
+        image_binary.save(output_path)
+        return output_path
+    except Exception as exc:
+        logger.error(f"Exception {exc} ocurred during image preprocessing.")
+        return file_path