TheAlgorithms · cclauss · Oct 16, 2020 · Oct 6, 2020 · Oct 6, 2020 · Oct 6, 2020
diff --git a/computer_vision/meanthreshold.py b/computer_vision/meanthreshold.py
@@ -0,0 +1,30 @@
+from PIL import Image
+
+"""
+Mean thresholding algorithm for image processing
+https://en.wikipedia.org/wiki/Thresholding_(image_processing)
+"""
+
+
+def mean_threshold(image: Image) -> Image:
+    """
+    image: is a grayscale PIL image object
+    """
+    height, width = image.size
+    mean = 0
+    pixels = image.load()
+    for i in range(width):
+        for j in range(height):
+            pixel = pixels[j, i]
+            mean += pixel
+    mean //= width * height
-    mean = 0
-    pixels = image.load()
-    for i in range(width):
-        for j in range(height):
-            pixel = pixels[j, i]
-            mean += pixel
-    mean //= width * height
+    total = sum(sum(pixel for pixel in row) for row in image.load())
+    mean = total // (width * height)
-    mean = 0
-    pixels = image.load()
-    for i in range(width):
-        for j in range(height):
-            pixel = pixels[j, i]
-            mean += pixel
-    mean //= width * height
+    total = sum(sum(pixel for pixel in row) for row in image.load())
+    mean = total // (width * height)
+
+    for j in range(width):
+        for i in range(height):
+            pixels[i, j] = 255 if pixels[i, j] > mean else 0
+    return image
+
+
+if __name__ == "__main__":
+    image = mean_threshold(Image.open("path_to_image").convert("L"))
+    image.save("output_image_path")