def detectEdges(image, amount):

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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The edge-detection function (detectEdges) described in Chapter 7 and shown below returns a black and white image. Think of a similar way to transform color values so that the new image is still in its original colors but the outlines within it are merely sharpened.

def detectEdges(image, amount):
    """Builds and returns a new image in which the edges of
    the argument image are highlighted and the colors are
    reduced to black and white."""
    def average(triple):
        (r, g, b) = triple
        return (r + g + b) // 3
 
    blackPixel = (0, 0, 0)
    whitePixel = (255, 255, 255)
    new = image.clone()
    for y in range(image.getHeight() - 1):
        for x in range(1, image.getWidth()):
            oldPixel = image.getPixel(x, y)
            leftPixel = image.getPixel(x - 1, y)
            bottomPixel = image.getPixel(x, y + 1)
            oldLum = average(oldPixel)
            leftLum = average(leftPixel)
            bottomLum = average(bottomPixel)
            if abs(oldLum - leftLum) > amount or \
                abs(oldLum - bottomLum) > amount:
                new.setPixel(x, y, blackPixel)
            else:
                new.setPixel(x, y, whitePixel)
    return new

Then, define a function named sharpen that performs this operation. The function should expect an image and two integers as arguments. One integer should represent the degree to which the image should be sharpened. The other integer should represent the threshold used to detect edges.

(Hint: A pixel can be darkened by making its RGB values smaller.)

Expert Solution
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NOTE: Code_indentation_is_very_important_for_python_code_execution.

Screenshot of code:

#Header file section for image module. from images import Image #Function defition of edge detection: This function #is used#create a duplicate of the image for y in range (image.getHeight () -1): for x in range (1, image.getWidth() -1): #Row major

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