(i) False - The Hough Transform is not a type of Fourier Transform. While both are used for feature extraction in image processing, they work in different ways. The Fourier Transform is used for frequency domain analysis, while the Hough Transform is used for shape detection.

(ii) False - The Hough Transform is not an energy minimization transform. It is a feature extraction technique used in image analysis, computer vision and digital image processing. Its purpose is to find imperfect instances of objects within a certain class of shapes by a voting procedure.

(iii) True - The Hough Transform does find groups of collinear pixels. It is particularly used for detecting lines, circles or other parametric curves in an image. It does this by a method of voting, where each pixel votes for all the curves that could pass through it, and the curves with the most votes are considered to be present in the image.

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(i) False - The Hough Transform is not a type of Fourier Transform. While both are used for feature extraction in image processing, they work in different ways. The Fourier Transform is used for frequency domain analysis, while the Hough Transform is used for shape detection.

(ii) False - The Hough Transform is not an energy minimization transform. It is a feature extraction technique used in image analysis, computer vision and digital image processing. Its purpose is to find imperfect instances of objects within a certain class of shapes by a voting procedure.

(iii) True - The Hough Transform does find groups of collinear pixels. It is particularly used for detecting lines, circles or other parametric curves in an image. It does this by a method of voting, where each pixel votes for all the curves that could pass through it, and the curves with the most votes are considered to be present in the image.

Knowee AI · Accepted Answer

(i) False - The Hough Transform is not a type of Fourier Transform. While both are used for feature extraction in image processing, they work in different ways. The Fourier Transform is used for frequency domain analysis, while the Hough Transform is used for shape detection.

(ii) False - The Hough Transform is not an energy minimization transform. It is a feature extraction technique used in image analysis, computer vision and digital image processing. Its purpose is to find imperfect instances of objects within a certain class of shapes by a voting procedure.

(iii) True - The Hough Transform does find groups of collinear pixels. It is particularly used for detecting lines, circles or other parametric curves in an image. It does this by a method of voting, where each pixel votes for all the curves that could pass through it, and the curves with the most votes are considered to be present in the image.

Consider the Hough Transform. Which of the following statements is/are true, ifany?(i) It is a type of Fourier Transform(ii) It is an energy minimization transform(iii) It finds groups of collinear pixels

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