Q. Marr hildreth method was introduced for

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Q. When the desired object is detected segmentation should be

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Q. Similarity approach of segmentation depends upon

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Q. For edge detection we combine gradient with

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Q. Lines are referred as

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Q. LOG stands for

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Q. Summation square and square root are called

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Q. The magnitude of vector is its

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Q. Second derivative approximation says that values of constant intensities must be

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Q. Gradient image is formed by the component

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Q. Double line effect is produced by

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Q. Local averaging

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Q. Digital images have edges that are

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Q. Edges arise between thin objects and backgrounds are

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Q. For edge detection we observes

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Q. For diagonal edge detection we use

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Q. Thresholding is the example of

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Q. Algorithm stating that boundaries of the image are different from background is

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Q. Intersection between zero intensity and extreme of second derivative is called

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Q. Edge detection has fundamental

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