Description

AuE 8200: Machine Perception and Intelligence
▪ This document file (with answers), and with your program results/visualization;
▪ A .zip file of source code (and data if any) with names indicating question number;

Question 1)
[Sampling/2D-Convolution – 15 pts] Download the image “Lenna.jpg” from the hyperlink.
(Lenna or Lena image is a standard test image widely used for image processing since 1973.)

1-1) Convert the image from RGB to gray, using a standard RGB-intensity conversion approach like NTSC, and store the converted image “LennaGray.jpg” as an 8-bit gray image. (2 pts)

1-2) Down-sampling image “LennaGray.jpg” from size 256×256 to 64×64. (3 pts) Perform the down-sampling and visualize your result.

1-3) Implement the convolution (using basic arithmetic operations only, rather than build-in conv()) of Sobel kernel on the “LennaGray.jpg” for edge detection, visualize and comment your detection result. (10 pts)

Question 2)
[Histogram Equalization – 15 pts.] Take the converted gray image “LennaGray.jpg”.

2-1) Perform histogram analysis and visualize histogram distribution (2 pts);

2-2) Calculate and visualize accumulative histogram distribution (3 pts);

2-3) Implement a function to perform histogram equalization for this image, visualize your histogram-equalized image and its histogram distribution. Comments the difference between the two images before/after histogram equalization. (10 pts);

Question 3)
[Line Detection – 30 pts] Download the image “ParkingLot.jpg” from the hyperlink. Note: For this question, you are free to use any 3rd party libraries.

3-1) Apply and visualize histogram analysis, then find a proper threshold to convert the image to a binary image. (2 pts)

3-2) Apply Hough transformation or other line detection approach to detect multiple lines in the image (You select a threshold for the voting matrix). Visualize the lines in the image space (just as: we saw lines there) and in the transformed space (like in Polar space that we introduced in the class) respectively. (5 pts)

3-3) Comment on: will the two lines as two sides of a particular park space be parallel or not, explain why? (3 pts)

Question 4)
Attention: You course Final project topic might be raised from your HW surveys. [Survey – 40 pts] Write a 2~3 pages survey report on a specific 2D-data measurement/detection problem related to automotive engineering.
• Please targeting at a specific 2D-detection goal/object. e.g.: lane detection, traffic sign detection, pedestrian detection, drivable area detection, a B-scan inspection for a manufacturing component, material characterization using microscopy image, et al. It is not limited to camera data.
• The detection target needs to be specific, rather than generic such as ‘Obstacle’ since it is not a specific target.
The grading of this question is based on the contents in the aspects of:
– The importance of measuring this target (5);
– The challenges of measuring this target (5);
– Existing approaches of measuring this target (15);
– Existing problems of these existing approaches (10);
– There will be other grading factors (such as novelty, organization, et al) (5);
* Attention: You are encouraged to include any drawing/table in the report;
* This survey is more focusing for the sensing and measurement of a 2D physical quantity or object, rather than comparing multiple 2D sensing modalities.
* You should not literally copy sentences from reference, and use “…” [1] to mark it if you really have to literally cite few sentences. For citations, use brackets （e.g. [1]) in the end of your statements, with reference list in the end of the report.