11. If the images are displayed using 8-bits, then, what is the range of the value of an image if the image is a result of a subtraction operation?
A. 0 to 255
B. 0 to 511
C. -255 to 0
D. None of the mentioned
Answer: D
The range of a result of a subtracted image is -255 minimum to 255 maximum if the 8-bit channel is used to display the original images.
12. The subtracted image needs to be scaled if the 8-bit channel is used to display the subtracted images. So, the method of adding 255 to each pixel and then dividing by 2, has certain limits. What is/are those lim its?
A. Very complex method
B. Very difficult to implement
C. The truncation inherent in the division by 2 causes a loss of inaccuracy
D. All of the mentioned
Answer: C
The given method is quite simple and easy to implement, however, it has the limitation of accuracy loss because of truncation inherent in the division by 2 and also that it doesn’t ensure the full range usage.
13. Which of the following are/are the fundamental factors that need tight control for difference-based inspection work?
A. Proper registration
B. Controlled illumination
C. Noise levels should be low enough so that the variation due to noise won’t affect the difference value much
D. All of the mentioned
Answer: D
Proper Registration does special marking into the product in case two images are identical so as the difference won’t create any sense.
Controlled Illumination is important because changes in illumination can affect dramatically the difference in image values.
Noise levels of a difference image must be low enough so that the variation due to noise won’t affect the difference value much.
14. When can two random variables be uncorrelated?
A. Their covariance is 0
B. Their covariance is 1
C. Their covariance is -1
D. None of the mentioned
Answer: A
The covariance of two random variables x i and x j given by: E [(x i – m i) (x j – mj)], E {.} is the expected value of the argument and m is the mean. If this covariance turns out to be 0, the variables are uncorrelated.
15. In the Image Averaging enhancement method assumptions are made for a noisy image g(x, y). What are/are those?
A. The noise is correlated at every pair of coordinates (x, y)
B. The noise has an average value of 1 at every pair of coordinates (x, y)
C. All of the mentioned
D. None of the mentioned
Answer: D
In Image, Averaging enhancement method assumptions are made for a noisy image g(x, y) that at every coordinate (x, y) the noise has 0 average value and must be uncorrelated.
16. The standard deviation ‘σ’ at any point in image averaging: σḡ(x, y) = 1/√K σɳ(x, y), where ḡ(x, y) is the average image formed by averaging K different noisy images and ɳ(x, y) is the noise added to an original image f(x, y). What is the relation between K and the variability of the pixel values at each location (x, y)?
A. Increase in K, decreases the noise of pixel values
B. Increase in K, increases the noise of pixel values
C. Decrease in K, decreases the noise of pixel values
D. Decrease in K, increases the noise of pixel values
Answer: A
As K increases, E {ḡ(x, y)} the expected value approaches f(x, y) the original image, i.e. decreasing the noise component.
17. A filter is applied to an image whose response is independent of the direction of discontinuities in the image. The filter is/are ________
A. Isotropic filters
B. Box filters
C. Median filter
D. All of the mentioned
Answer: A
The isotropic filter is rotation invariant because it has the same response when applied to the image first and then after rotating the image.
18. In isotropic filtering, which of the following is/are the simplest isotropic derivative operator?
A. Laplacian
B. Gradient
C. All of the mentioned
D. None of the mentioned
Answer: A
An isotropic filtering is an example of a second-order derivative for enhancement and uses Laplacian as the simplest derivative operator, while gradient is used with first derivatives.
19. The Laplacian is which of the following operator?
A. Nonlinear operator
B. Order-Statistic operator
C. Linear operator
D. None of the mentioned
Answer: C
Derivatives of any order are linear operations and since Laplacian is the simplest isotropic derivative operator, so is a linear operator.
Order-Statistics operators are nonlinear operators.
20. A Laplacian for an image f(x, y) is defined as: is given by ________
A. [f(x + 1, y) + f(x – 1, y) – 2f(x, y)] and [f(x, y + 1) + f(x, y – 1) – 2f(x, y)] respectively
B. [f(x + 1, y + 1) + f(x, y – 1) – 2f(x, y)] and [f(x , y + 1) + f(x – 1, y) – 2f(x, y)] respectively
C. [f(x, y + 1) + f(x, y – 1) – 2f(x, y)] and [f(x + 1, y) + f(x – 1, y) – 2f(x, y)] respectively
D. None of the mentioned
Answer: A
For a Laplacian given by:∇2 f=
Applying second order derivative in x direction (∂2 f)/∂x2 = [f(x + 1, y) + f(x – 1, y) – 2f(x, y)], and
Applying second order derivative in y direction (∂2 f)/∂y2 = [f(x, y + 1) + f(x, y – 1) – 2f(x, y)].
