EL561 Assignment 3 Answer all THREE questions. 1. Figure 1 illustrates a simple test image. The.

EL561 Assignment 3 Answer all THREE questions. 1. Figure 1 illustrates a simple test image. The numbers represent the gray-scale intensities of the pixels. (a) Determine the gray-level cooccurrence matrix (GLCM) where the pixel offset is defined by _ = 1 and _ = 45 (also described as [1, 1]). Hence, estimate the texture features (i) entropy, (ii) uniformity contrast, (iii) energy for the image in Figure1. [7 marks] (b) What would be the texture energy if the offset is changed to _ = 1 and _ = 90. [3 marks] Figure 1 2. A Self-Organising Map has two neurons each with four inputs. The

EL561 Assignment 3 Answer all THREE questions. 1. Figure 1 illustrates a simple test image. The numbers represent the gray-scale intensities of the pixels. (a) Determine the gray-level cooccurrence matrix (GLCM) where the pixel offset is defined by _ = 1 and _ = 45 (also described as [1, 1]). Hence, estimate the texture features (i) entropy, (ii) uniformity contrast, (iii) energy for the image in Figure1. [7 marks] (b) What would be the texture energy if the offset is changed to _ = 1 and _ = 90. [3 marks] Figure 1 2. A Self-Organising Map has two neurons each with four inputs. The initial values of the weights is shown in Table 2 where the first column shows the values connecting each of the four inputs to neuron 1 respectively and the second column shows the values for each of the four inputs connected to neuron 2. Assuming that the learning rate initially is _ = 0.5 and the neighbourhood radius is set to zero, iterate through the first two epochs (only) of the training that would occur for the binary input patterns 1,0,0,1 and 0,1,1,0 respectively and hence determine the new weight information. Assume the learning rate geometrically decreases after every epoch by _(_+1) = 0.5 _(_). Table 2 [ You must show all intermediate steps of calculations in your submission.] [10 marks] 3. A particular biometric authentication system is being tested. The test set-up involves both genuine users and impostors and a summary of the decisions made by the system is shown below. Calculate the False Acceptance Rate (FAR), False Rejection Rate (FRR) and overall Accuracy of this system (in %). Number of genuines accepted 4679 Number of impostors accepted 101 Number of genuines rejected 389 Number of impostors rejected 31751 [5 marks] 0 0 1 1 0 0 1 1 0 2 2 2 2 2 3

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