Create a computer vision system using decision tree algorithms to solve a real-world problem : Hough transform theory

The video tutorial introduces the Hough Transform, a technique in computer vision used to detect lines in images. It explains the mathematical representation of lines using rho and Theta, and how these parameters are used in the Hough Transform. The tutorial transitions from image space to Hough space, demonstrating the voting mechanism for line detection. A practical example is provided, followed by an implementation of the Hough Transform in OpenCV, highlighting its application in detecting lane lines in images.

What is the difference between image space and half space in the context of line detection?

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How can the Hough transform be applied in real-world applications such as autonomous driving?

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What role does the threshold value play in detecting lines using the Hough transform?

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Explain the concept of region of interest masking in relation to the Hough transform.

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