Second derivative approximation says that value at end of ramp must be

DIGITAL IMAGE PROCESSING (DIP)- IMAGE SEGMENTATION MCQ

• Digital functions\' derivatives are defined as
• For line detection we use mask that is
• Gradient computation equation is
• For finding horizontal lines we use mask of values
• If the inner region of the object is textured then approach we use is
• The horizontal gradient pixels are denoted by
• To avoid the negative values taking absolute values in lapacian image doubles
• First derivative approximation says that values of constant intensities must be
• For finding lines at angle 45 we use mask of values
• Second derivative approximation says that values along the ramp must be
• Ri is a connected set, where is
• Gradient magnitude images are more useful in
• Image having gradient pixels is called
• In laplacian images light shades of gray level is represented by
• For noise reduction we use
• Diagonal lines are angles at
• Transition between objects and background shows
• Horizontal lines are angles at
• Standard deviation is referred to as noiseless if having the value
• For edge detection we use
• Step edge transition is between pixels over the distance of
• Sobel gradient is not that good for detection of
• Smoothness reduced the bricks of
• Second derivative approximation says that it is nonzero only at
• Method in which images are input and attributes are output is called
• Computation of derivatives in segmentation is also called
• Model of lines through region is called
• Transition of intensity takes place between
• Averaging is analogous to
• Response of derivative mask is zero at
• Subdivision of the image depends upon the
• One that is not a method of image segmentation is
• Discontinuity approach of segmentation depends upon
• On ramp and step second derivatives produce
• Point detection is done using filter that is
• Second derivatives are zero at points on
• Two regions are said to be adjacent if their union forms
• 8bit image has intensity levels of
• Sobel operators were introduced in
• Blurring attenuate the
• A line is viewed as
• Sobel is better than prewitt in image
• Intensity\'s local changes can be detected through
• For line detection we assume that lines are
• Example of similarity approach in image segmentation is
• The preferred direction of mask is weighted with the
• Points other than exceeding the threshold in output image are marked as
• In laplacian images dark shades of gray level is represented by
• Pixels where intensity changes abruptly are called
• Isolated point is also called
• Points exceeding the threshold in output image are marked as
• Example of discontinuity approach in image segmentation is
• First derivative approximation says that values of intensities at the onset must be
• Image segmentation is also based on
• Image whose principle features are edges is called
• Vertical lines are angles at
• If R is the entire region of the image then union of all segmented parts should be equal to
• Mask\'s response to zero means
• Lines in an image can be oriented at angle
• Laplacian images need
• For point detection we use
• Textured inner region of the object produces
• If the standard deviation of the pixels is positive, then sub image is labeled as
• Thresholding gives the
• Marr hildreth method was introduced in
• Segmentation is a process of
• Log function is also called
• Segmentation algorithms depends on intensity values\'
• Sudden changes in intensity produces peak in
• Ideal edges occur over the distance of
• Image intensities are normally ranged to
• Edge detector method is used to detect
• Accuracy of image segmentation can be improved by the type of
• During segmentation every pixel of an image should be in
• The vertical gradient pixels are denoted by
• For line detection we use
• Marr hildreth method was introduced for
• When the desired object is detected segmentation should be
• Similarity approach of segmentation depends upon
• For edge detection we combine gradient with
• Lines are referred as
• LOG stands for
• Summation square and square root are called
• The magnitude of vector is its
• Second derivative approximation says that values of constant intensities must be
• Gradient image is formed by the component
• Double line effect is produced by
• Local averaging
• Digital images have edges that are
• Edges arise between thin objects and backgrounds are
• For edge detection we observes
• For diagonal edge detection we use
• Thresholding is the example of
• Algorithm stating that boundaries of the image are different from background is
• Intersection between zero intensity and extreme of second derivative is called
• Edge detection has fundamental
• Regions of the image must be
• More smoothness is created by the mask of size
• The direction of angle to the gradient is
• Second derivative approximation says that value at end of ramp must be
• In the sense of predicate two regions of the image must be
• If all lines in the direction of defined direction of mask are wished to be found then we use
• If inside the boundary is white otherwise black predicate is
• One angle at which the lines in an image are not oriented is
• Edge detection is based on
• Dividing image into its objects is called
• The coefficients of masks sum to
• Sum of coefficients of derivative mask is
• Fine details can be reduced by
• The sum of LOG filter coefficients should be
• Canny edge detection algorithm is based on
• First derivatives are zero at points on
• The resolution of the image (12x12) is
• In laplacian images mid gray level is represented by
• Locating the center of thick edges we use
• Strong Heat signatures can be detected using
• Second derivatives have stronger response to
• Edge pixels lie on darker or bright side of image can be determined by the
• First derivatives in image segmentation produces
• Edge localization id edge detection\'s
• To avoid the negative values in lapacian image we use only
• Masks for detection of specific lines are called
• Line whose length and width is of one pixel is called
• Detection of edge points is edge detection\'s
• Intersection of two connected sets of an image should be
• Isotropic detectors are independent of
• For finding vertical lines we use mask of values
• For diagonal edge detection we use 2D mask of
• For finding lines at angle -45 we use mask of values
• Gradient vector is also called
• First and second derivatives can be computed using
• First derivatives are positive at points on
• For finding edge strength approach that is used is
• Image segment methods are of
• Thresholding gradient image produces good
• Laplacian detector is
• Slope of the ramp and degree of blurring are
• One that is more sensitive to noise is
• Success of image segmentation is determined by its
• Second derivatives in image segmentation produces
• Thresholding formulation measures difference between
• Lines not assumed as thin as referred to as
• If all the regions are labeled with same intensity then it produces
• Electronic components determines the image\'s
• Segmentation is difficult for images that are
• First derivative approximation says that value at ramp must be
• Edge models are classified based upon their
• Gradient of an image is obtained through
• Examples of similarity approach in segmentation are
• What is the Euler number of the image shown below?
• What is the Euler number of the region shown in the figure below?
• The chain code for the following shape is given as:
• What does the total number of pixels in the region defines?
• What is the unit of compactness of a region?
• For which of the following regions, compactness is minimal?
• Compactness is insensitive to orientation
• Which of the following measures are not used to describe a region?
• We cannot use normalized area as one of the region descriptor
• What is the study of properties of a figure that are unaffected by any deformation?
• On which of the following operation of an image, the topology of the region changes?
• Topological properties don’t depend on the distance measures
• What is the Euler number of a region with polygonal network containing V,Q and F as the number of vertices, edges and faces respectively?
• The texture of the region provides measure of which of the following properties?
• Structural techniques deal with the arrangement of image primitives
• Which of the following techniques is based on the Fourier transform?
• The length of a boundary is one of the boundary descriptors
• Which of the following of a boundary is defined as the line perpendicular to the major axis?
• Which of the following is the useful descriptor of a boundary, whose value is given by the ratio of length of the major axis to the minor axis?
• The term, Curvature is defined as:
• If the boundary is traversed in the clockwise direction, a vertex point ‘p’ is said to be a part of the convex segment if the rate of change of slope at ‘p’ is:
• A point ‘p’ is said to be corner point, if the change of slope is less than 10 degrees
• Based on the 4-directional code, the first difference of smallest magnitude is called as:
• The order of shape number for a closed boundary is:
• What is the order of the shape number of a rectangular boundary with the dimensions of 3×3?
• Statistical moments are used to describe the shape of boundary segments quantitatively
• Which of the following techniques of boundary descriptions have the physical interpretation of boundary shape?
• Statistical moments is sensitive to rotation

This question belongs to these collections

• DIGITAL IMAGE PROCESSING (DIP)- IMAGE SEGMENTATION MCQ

Similar questions