Title: Star Matching from Images
1Star Matching from Images
- Computer Vision Final Project
- by Wei-Chao Chen
2Problem Statement
- Goal
- Take pictures in the night sky.
- Match the pictures with star catalog.
- Condition Requirements
- Camera parameter are unknown a priori.
- Pictures are free with large bright objects
(e.g., moon). - Stars in each pictures are related by linear
translation.
3Sample Picture
4Difficulty in the Problem
- Too many free variables..
- Camera parameters, time, location, orientation
when taking the picture. - Matching can be ambiguous..
- Except for relative brightness and color, stars
have no other salient features. - Sensitive to noise..
- Bad pixels can be regarded as stars.
5A Solution
- Match by looking at similar triangles between two
images. - Each image with N stars generates C(N, 3)
triangles. - Each star can have up to N(N-1)/2 matches.
- The stars pair with higher vote of matches are
considered as matches.
6A Solution
4
2
a1
1
T1(a1, b1, c1) gt(a1/c1, b1/c1)
3
b1
c1
1
3
4
2
The aspect ratio of each triangle forms a
2D tuple and matching is done at the tuple space.
7Results
- Implementation
- ANSI C/C
- Steps
- Star Detection-Matching-Output
- Running Speed
- Generally below 5 seconds on PII PCs (including
Disk I/O)
8Results - Star Detection
One Input Image
Detected Stars
9Results - RotationTranslation
Red Image 1 Green Image 2 Yellow Match
10RotateTrans.ScalingClipping
Red Image 1 Green Image 2 Yellow Match
Overlapped Region
11Rigid Trans. Small Noise
Red Image 1 Green Image 2 Yellow Match
Noise
Noise
12Algorithm Problems
Speckles on image 2 results in algorithm instabili
ty.
Red Image 1 Green Image 2 Yellow Match
13Algorithm Problems
Radial Distortion caused the algorithm to break.
Red Image 1 Green Image 2 Yellow Match
14References
- Valdes et al., FOCAS Automatic Catalog Matching
Algorithms, in Publications of Astronomical
Society of the Pacific, 1995 November. - Griesen et al., Representation of World
Coordinates in FITS, www.cv.nrao.edu/fits/documen
ts/wcs/wcs.html