You can turn in your assignment up until 5:00pm on 2/27/15. You should
hand in both a hardcopy and electronic copy of your solutions. Your hardcopy
submission should include printouts of four code files:
illusion.m, grades.m, energy.m, and
To save paper, you can cut and paste all of your code files into one script, but your
electronic submission should contain the separate files. Your electronic
submission is described in the
section Uploading your completed work.
assign3_exercisesfolder from the cs112d directory onto your Desktop. This folder contains two code files and three image files for Lab #4 and the exercises in this assignment.
When you have completed all of the work for this assignment, your
folder should include two code files for the exercises,
assign3_problems folder should contain two code files named
recognize.m. Use Fetch or WinSCP to connect to your
personal account on the CS file server and navigate to your
cs112/drop/assign3 folder. Drag your
assign3_problems folders to this drop folder. More details about this process
can be found on the webpage on Managing Assignment Work.
The so-called Thatcher illusion was first demonstrated by the psychologist Peter Thompson in 1980. Follow this link to a fun page that allows you to experience the illusion yourself. The photographs of people on this page have been altered so that their eyes and mouth are flipped upside-down. When you view the altered images upside-down, you hardly notice, but when you flip the images upright, the result can look like something out of a horror movie! You can read more about the Thatcher illusion, or Thatcher effect, at this Wikipedia page. In this exercise, you'll create your own demonstration of this effect.
To begin, run the script named
loadImages.m in the
folder, which loads two images that are assigned to the variables
clinton in the MATLAB Workspace. For your demonstration,
you can just choose one of these images, and you only need to flip the eyes upside-down. View
your selected image with
imtool and determine the coordinates for the corners of
a rectangular region containing the eyes.
Create a script named
illusion.m in the
folder, and add code to this script to create and display images that capture this illusion.
In particular, your code should use
subplot to create a 2 x 2 grid of four images,
displayed as described below:
It does not matter where you place the four images within the subplot. The Wikipedia page shows a sample display that is similar to what you should create for this problem. Tip: create a new variable to store the modified image that has the eyes upside-down.
Add comments to your
illusion.m code file, with the names of you and
your partner, the date, and a description of the task coded, and upload it with the other files in your
assign3_exercises folder, when turning in Assignment 3.
The following table provides the semester grades for six CS112 students:
Open the file called
grades.m in the
This file creates a matrix named
scores that contains the information in the above table, and two
cell arrays called
measures that store the
names of the students and the components of the grade. Add code to the
file to perform the tasks listed below. Try to write code that is as compact
as possible but still readable and understandable.
scoresmatrix with each student's final course score. The course score is calculated in CS112 as follows: Homework counts 40%, Participation 5%, Exams are each 20% and the Final Project is 15%.
avgScoreswith the average (across students) of each component of the final grade, as well as the average final course grade.
Add comments to your
grades.m file describing each of the above tasks, and also
add comments with the names of you and your partner.
In this problem, you will explore data on U.S. energy production and consumption
using energy statistics available from the Energy Information Administration
(EIA) within the U.S. Department of Energy. The
assign3_problems folder in
contains two Excel spreadsheets,
that were downloaded from the
Energy Overview page
at the EIA website. These spreadsheets contain both numerical and textual data
related to the production and consumption of various energy sources over the
years 1949-2006, which you can view by opening these files in Excel. Unfortunately,
a separate MATLAB toolbox is needed to load data from complex spreadsheets such
as this, and the public computers at Wellesley do not currently have this toolbox.
We can, however, read Excel spreadsheets that contain only numerical data into
MATLAB. The two files,
consume.xls, contain most of the numerical data from the original
EIA spreadsheets. These files can be read into MATLAB using the
productionData = xlsread('produce.xls');
The contents of both
be loaded into matrices with 58 rows corresponding to the years 1949-2006. The matrix created
produce.xls has 14 columns representing (1) year, (2) coal,
(3) natural gas, (4) oil, (5) NGPL (natural gas plant liquids), (6) total fossil fuels,
(7) nuclear, (8) hydroelectric, (9) geothermal, (10) solar, (11) wind, (12) biomass,
(13) total renewable energy and (14) total energy produced. The matrix created from
contains 13 columns representing (1) year, (2) coal, (3) natural gas, (4) oil, (5) total
fossil fuels, (6) nuclear, (7) hydroelectric, (8) geothermal, (9) solar, (10) wind,
(11) biomass, (12) total renewable energy and (13) total energy consumed. The file
population.mat in the
assign3_programs contains a column vector
of the U.S. population over the years 1949-2006.
Create a script file named
energy.m in the
folder that reads in the contents of the
and performs the following tasks:
In a single figure window, plot the following data in one graph: amount of coal, gas,
oil, NGLP, nuclear and total renewable energy produced, and the amount of coal, gas and
oil consumed (note that the U.S. consumes all of the renewable energy sources that it
produces). Plot this data as a function of the year. There should be 9 line plots drawn
in a single plotting area.
Complete this code without creating any additional variables - each call to
plot function should refer directly to the two matrices storing the data.
Use one line style for all of the production data and a different line style for all of
the consumption data, and use different colors for the plots.
Add a title, axis labels and legend for the graph. Note that you can drag the corners of
the figure window to expand its size, and drag the legend to a new location if desired.
Open a second figure window and create four graphs that display the following information
for each year. In each case, the year can be plotted on the x axis. Use
define a 2 x 2 grid of plotting areas for drawing the four graphs.
These observations are unfortunately a little disturbing...
Add comments to your
energy.m code file.
Wellesley College is proud to have some very distinguished alumnae! For this
problem, you'll write a program to recognize the faces of three of our special
graduates: Madeleine Albright '59, Hillary Clinton '69 and Pamela Melroy '83.
assign3_problems folder contains three face images whose
identity is assumed to be known (
albright.jpg, clinton.jpg, melroy.jpg)
and three face images to be recognized by your program (
face2.jpg, face3.jpg). The file
initial code that loads the six face images into variables in the MATLAB workspace
and displays them using
(the top three images are the known faces and the bottom images are the
One strategy we can use to recognize an unknown image is to measure the difference between the pattern of brightness values in the unknown image and the patterns of brightness in each of a set of known images. We can then select the known image that represents the closest match. Consider a very simple example where we have two known image patterns corresponding to a vertical or horizontal edge, as shown below:
Suppose we are given a "mystery" image and want to determine whether it has a vertical or horizontal edge pattern:
We can first calculate the element-by-element difference between each known image and our new mystery image:
We are really only interested in the amount of difference between the
two patterns, so we can take the absolute value of the differences (this can be done
abs function in MATLAB):
On average, the brightness values in the mystery image differ from the brightness values in the vertical image by only 0.2, while the brightness values differ from those in the horizontal image by 0.5 (on average). Thus there is a closer match between our mystery image and the vertical image, so we recognize it as a vertical edge.
Using this strategy for calculating how well the pattern of brightnesses
match between two images, first add code to the
code file to calculate the average difference between the
face1 image and each of the three known face images stored in
albright, clinton and
add code to determine which of the three known faces is the best match to
face1 using the three average differences that you calculated.
Print a message indicating the identity of
face1. Then repeat this
process for the unknown faces stored in
Tip: cutting and pasting, and then making small modifications to
the copied code, will save a lot of time! Your program should be
able to recognize each of the three faces correctly.
Real face recognition systems face many challenges: hair styles change and faces
appear with different expressions, poses and directions of gaze, and with different
backgrounds and lighting. To cope with variations in hair styles and backgrounds,
the recognition process is often based on a cropped area of the face that excludes
the hair and background. For this part of the problem, you'll attempt to recognize
the three faces using a cropped region of the faces that includes only the eyes,
nose and mouth. The original images (the images in the top row of Figure 1 above,
labeled with each person's name) were carefully constructed so that they
have the same overall size, with the region around the eyes, nose and mouth
covering roughly the same area of each image. Create a set of six new variables
that each store a small region of one of the original face images containing only the
eyes, nose and mouth. Use the same coordinates for the upper left and lower
right corners of the rectangular region that you select for all six images.
imtool to help identify appropriate coordinates
(as you move your mouse over the image displayed with
(X,Y) coordinates of the mouse are displayed in the lower left
corner of the display window - remember that the order of these
coordinates should be reversed when specifying the row and column of the
corresponding locations of the matrix storing the image). Using
imshow, display the six cropped images, as shown in the
example below (again consider copying, pasting and modifying code here!):
Repeat your code to recognize the cropped versions of the
face1, face2 and
face3 images. Tip: copy and paste the code that you created to recognize
the full images, and then make modifications to this code to use the cropped images
instead. Are you still able to recognize each of the three faces correctly?
Note: you may have found the code in this problem to be very repetitious! This provides good motivation for learning our next topics: user-defined functions and loops.
Be sure to add comments to your
recognize.m code file, describing
the code. Also add comments at the top of the file indicating your
name and that of a partner, and any collaborators.