Q. Edge detection is based on

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Q. Dividing image into its objects is called

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Q. The coefficients of masks sum to

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Q. Sum of coefficients of derivative mask is

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Q. Fine details can be reduced by

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Q. The sum of LOG filter coefficients should be

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Q. Canny edge detection algorithm is based on

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Q. First derivatives are zero at points on

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Q. The resolution of the image (12x12) is

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Q. In laplacian images mid gray level is represented by

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Q. Locating the center of thick edges we use

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Q. Strong Heat signatures can be detected using

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Q. Second derivatives have stronger response to

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Q. Edge pixels lie on darker or bright side of image can be determined by the

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Q. First derivatives in image segmentation produces

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Q. Edge localization id edge detection's

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Q. To avoid the negative values in lapacian image we use only

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Q. Masks for detection of specific lines are called

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Q. Line whose length and width is of one pixel is called

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Q. Detection of edge points is edge detection's

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