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The edge-detection function ( detectEdges ) described in Chapter 7 an 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 bu the outlines within it are merely sharpened.

The edge-detection function ( detectEdges ) described in Chapter 7 an 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 bu the outlines within it are merely sharpened.

Database System Concepts
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
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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 (0, 0, 0) (255, 255, 255) blackPixel = whitePixel = new = image.clone() for y in range(image.getHeight() - 1): for x in range(1, image.getWidth()): image.getPixel(x, y) image.getPixel(x oldPixel = 1, y) leftPixel bottomPixel = image.getPixel(x, y + 1) oldLum = average(oldPixel) leftLum = average(leftPixel) bottomLum = average(bottomPixel) if abs(oldLum · abs (oldLum - bottomLum) > amount: new.setPixel(x, y, blackPixel) leftLum) > amount or \ 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.
Transcribed Image Text: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 (0, 0, 0) (255, 255, 255) blackPixel = whitePixel = new = image.clone() for y in range(image.getHeight() - 1): for x in range(1, image.getWidth()): image.getPixel(x, y) image.getPixel(x oldPixel = 1, y) leftPixel bottomPixel = image.getPixel(x, y + 1) oldLum = average(oldPixel) leftLum = average(leftPixel) bottomLum = average(bottomPixel) if abs(oldLum · abs (oldLum - bottomLum) > amount: new.setPixel(x, y, blackPixel) leftLum) > amount or \ 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.
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