



Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Material Type: Exam; Professor: Duric; Class: Computer Vision; Subject: Computer Science; University: George Mason University; Term: Unknown 1989;
Typology: Exams
1 / 5
This page cannot be seen from the preview
Don't miss anything!




Name:
Assume that a coordinate system with x-axis pointing right and a y-axis pointing up is added. The coordinates of the left bottom pixel are (0, 0). Compute the following parameters:
a) (3p) area, b) (3p) perimeter (describe your algorithm), c) (4p) center of mass, d) (10p) second order moments M 11 , M 20 , and M 02. e) (10p) central moments μ 11 , μ 20 , and μ 02.
a) (5p) Represent N so that it can be used by the GHT (Generalized Hough Transform) algorithm. b) (15p) Use GHT to find N in M. How many matches did you find? You can use the grid above for the GHT accumulator array. c) (10p) Use forward/backward pass algorithm to compute the distances of all points in M from the edge points of M. You can assume that the distance between any pair of 8-neighbors is 1. d) (15p) Use Chamfer matching to find N in M. Show all placements with scores lower than 10. You can assume that the placement of N is at the position of the topmost pixel of N. What are the best matches? e) (5p) Show how the distance transform array could be used to perform a Hausdorff dis- tance matching on N and M. Show the best match(es).
Template N, edge image M, and the GHT scores.
N and M GHT scores
Distance transform and Chamfer match scores
forward pass backward pass match score
Hausdorff distance matching