Create a computer vision system using decision tree algorithms to solve a real-world problem : Region of interest maskin

The video tutorial introduces the concept of region of interest (ROI) masking, particularly in the context of self-driving cars. It explains how ROI masking helps focus on specific areas of an image, such as lane lines or pedestrians, by creating a mask that highlights these regions. The tutorial covers the creation of masks, setting pixel values, and applying the end operation to extract the desired image areas. The end operation is likened to a multiplication process, where only the regions of interest are retained in the final image.

Why is it unnecessary to apply algorithms to areas of the image that do not contain the object of interest?

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What are the expected outcomes when multiplying the mask with the original image?

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