QUESTION 1: You are asked to write a program file that will be named as 'Q1.m'. This main '.m' file will contain all your work and a template (Q1_Empty.m) will be given to you beforehand to guide you for the asked tasks. In Q1, a function (named as "createSmoothedImage"), which returns you a smoothed randomly generated matrix (this matrix can be interpreted as an image when proper visualization built-in Matlab functions are used), will be given to you. A seed value is passed to "createSmoothedImage" to be able to guarantee the creation of the same image in every call of this function. You will be asked to write a Matlab code which applies intensity-based thresholding to this image. The elements of the matrix have already been normalized by using the mean and standard deviation of the convolved matrix elements. Please write the code file which realizes the asked tasks and creates the correct plots. An exemplary case outputs, in which the seed value is chosen as 4 , are given to you to be able compare validate your code. - You should run your code for the seed values 4,5 and 6 . You should put your obtained results and other required information to your report (a report template has already been given to you). Your report should include your results (images, graphs, text, etc.), as well as your comments about your code and your results. Separately you should add your code files to your final ZIP file. - You should write the code segment which show the Histogram of your image. - You should write the code segment which detects the peaks exceeding 2 and obtain the location information of these segmented blobs. - You should write the required code snippets for visualizing the segmented peaks (blobs) and their boundaries (on the original image as a contour-line). - The required figures for the seed value =4 case are given below for validation of your findings. - You should write the required code snippets to summarize the findings of your segmentation approach by printing the number of segmented peaks (also can be named as clusters), the area of the smallest and largest clusters. An exemplary command window output is also given below: There are 5 clusters in the image - Written by Gorkem The area of the largest cluster is 2348 pixels - Written by Gorkem The area of the smallest cluster is 3 pixels - Written by Gorkem