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日期:2020-10-10 11:05

Assignment 1: Image Processing and Computer

Vision (20%)

COMP 4180 Intelligent Mobile Robotics

FALL TERM 2020

Release Date: 17 September 2020

Due Date: 13th October 2020, 4 PM (UTC -6 Central Time)

Content

In this assignment, you will use the OpenCV 3.3x, a standard vision library to develop a vision

module to support capturing and manipulation of images and videos. This vision module will be

carried over from assignment to assignment as I mentioned in class. There could be several

solutions to these open-ended problems. So general assessment will not only be based on the

outcomes but also on functionality, efficiency, and style, e.g. how elegant your code is.

Object and Feature Tracking Using OpenCV Library

Implement a feature detector that can reliably detect the feature point and recognise objects such

as obstacle, region of soccer field, goal, etc. in RoboCup Humanoid League our Simurosot

competition. Motion Analysis and Object Tracking could be useful too.

1

Figure 1: SimuroSot Robo Challenge Obstacle Avoidance

Figure 2: Expected outputs.

Tasks

1. Download and install OpenCV 3.3.x in your Linux machine (Ubuntu 16.04).

2. Download the sample POV images here.

3. Preprocess the input image from the streaming camera, converting it to different colour

space (RGB, HSV, grayscale), blurring, and detecting edges (each of these is a call to an

OpenCV method – such as Canny() for canny edge detector). Documentation on the

methods can be found on the OpenCV site: http://docs.opencv.org/.

2

4. [3%] Goal Detection: Write a subroutine called findGoal find the goal from the soccer field

from the sample POV images, as shown in Figure 2. Hint: extract the green soccer field

from the background such as the floor and surrounding. For example: return (x,y,area)

5. [5%] Obstacle Detection: Write a subroutine called findObstacle to find the obstacles in the

soccer field as shown in Figure 1 and 2. This subroutine should return the position (in 2D

space) and size of the obstacle. You will need to use image processing methods such as

colour extraction, thresholding, shape recognition, and morphological operation. Hint: You

may use ApproxPolyDP to detect the contour of the obstacles.

6. [10%] Write another subroutine called drawField to detect lines segments in the soccer field

and draw coloured lines to differentiate various region of the field such as goal lines

(pink), touch line (blue), center circle (yellow), etc. to distinguish the output visually

as shown in Figure 2. You need to implement a geometric approach based on line segment

detector fast line detector, and/or corner detector. Hint: Hough Line Transform is too

expensive.

7. [2%] Write a 2-page report (11-point, Arial, single-space) to explain the implementation and

results based on task 4 to 6. Include some of image processing outputs as an image

pipeline in your report.

8. Make sure your codes are well commented in order to obtain full marks.

9. Machine learning approach is a plus!

Submission

This assignment shall be done individually.

You must submit all parts of the assignment before the due date and time. Create a zip or tgz

archive which includes all source code of your project. Your submission should extract into a

directory called <course number>_a1<student_number>.

Write a README file to explain anything you feel is necessary or important about your submission.

This may include special features/bugs of your program. Describe what parts of the assignment

you implemented. It is in your interest to simplify the job of the marker.

3

Submit/upload the archive to me via UMLearn. You have to agree to the honesty

declaration on “Checklist” at UMLearn before the submission.


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