the code we used was skimage python

Q 1(a) [6 Marks] Explain, in detail, the terms listed below. In each case, outline a specific example of how the image processing and analysis operation is used in practice. i. Cumulative Image Histogram. ii. Convolution for Image Processing. iii. Adaptive Thresholding. Q 1(b) [3 Marks] Starting with Image Formation, outline the main stages in a fully integrated Image Processing and Analysis engineering system, clearly outlining the role of each element. Q 1(c) [4 Marks] Using linear normalization based contrast stretching calculate the normalized output values for the input values of 148,149 and 150 . The normalization is to map the input range 100 to 200 to the output range 0 to 255 . Comment on the range of greyscale outputs generated using this normalization technique. Q 1(d) [6 Marks] Outline a robust, data driven sequence of image processing and analysis steps necessary to automatically find the number of objects in the grey scale image illustrated in Figure Q1.1. Your approach must be invariant to image rotation. Implement your solution using appropriate pseudo code and state any assumptions clearly. Comment on the robustness of your approach in the presence of Gaussian noise. Figure Q1.1: Grey scale image