Robust Localization, Classification, and Temporal Evolution Tracking in

Auroral Data

G. Germany * C.C. Hung †T. Newman * J. Spann ‡

* Univ. of Alabama in Huntsville† S. Polytechnic State Univ.

‡ MSFC

AISR Meeting, April 4-6, 2005

Visual Perception I

• What do you see?

from Torrans 99 (GMU) from Schiffman’s Sensation and Perception, 2000, as presented by Loken et al., Macalester Coll.

Visual Perception I

• What do you see?

from Torrans 99 (GMU) from Schiffman’s Sensation and Perception, 2000, as presented by Loken et al., Macalester Coll.

Gestalt = Form, a unit of perceptionNote: Avoid strict Gestaltism!

Visual Perception II: Some Gestalt

• Continuity

• Closure

• Proximity

• Similarity

EEEEEEEEEEFEEEEEEEEEE

A Problem: Finding Auroral Oval

UVI Image Region-Based Seg.

A Problem: Finding Auroral Oval

UVI Image Region-Based Seg.

* Incomplete

Toward a Better Solution?

• Exploit:

– Continuity

– Closure

– Proximity

– Similarity

Toward a Better Solution?

• Exploit:

– Continuity

– Closure

– Proximity

– Similarity

General Goal: Support Study of Aurora

• UVI Polar Datasets– 9M+ images!

• Exploitation Challenge

– OST (Germany Talk @ AISR05)• Queries based on:

– Sensor Location– Some Image Features:

• Integrated Intensity• Boundary Position• Image Quality

• Popular:– 1000/100

Specific Goal: Effective Retrieval

• UVI OST: Mining Pre-Processing

– Removes Non-Auroral Features

– Extracts Auroral Oval

• Inefficient

• Often fails

• Support Auroral Feature Search

– Shape-Based Processing to Localize Oval

– Better-support Auroral Feature Retrieval

Shape Recovery

• Our prior work:– Spheres– Cylinders– Cones– Ellipsoids– Paraboloids– Hyperboloids– Compound Structures

Exploiting Shape I

• Exploiting Shape: Preliminaries– What Shape?– Shape Invariant Descriptors

2 2 1Ax By Cxy Dx Ey

/ 2 / 2

/ 2 / 2

/ 2 / 2

A C D

C B E

D E F

/ 2

/ 2

A CJ

C B I A B

0, 0, 0 : ellipseJI

Exploiting Shape II: Experiments

• Shape Testing

– Manual Tracing

– Linear Least Squares Fitting

– Shape Invariant Extraction

97/0

11/0

5342

297

/011

/094

246

FittingsManually traced boundaryColorized Image Invar.

∆ = 2E-10J = 1E-9I = -8E-5∆/I < 0

∆ = 9E-9J = 2E-8I = -3E-4∆/I < 0

Some Fitting Results

Initial Work: Localization

• Hough-Based Processing– Democratic:

• Pixels Vote

– Example• y = mx + b

PixelA

y=ax+cy=px+q

y=fx+g

y=dx+e

Approx. Auroral Oval Boundary

• Thresholding with density examination– Thresholding value: (mean of the pixel intensities)

• LoG edge detection

99/006/093006 Thresholded image Dense part Boundary

Shape-based Detection

• Mod. Randomized Hough Transf. (MRHT) for ellipse:– Randomly Select Eedgels– Fit General Quadratic– Determine Shape– Ellipse Parameter Recovery (next page)– Parameter Space Decomposition

• 2D accumulate array for center• 2D accumulate array for axes• 1D accumulate array for orientation

• MRHT for ellipse– Recover:

0 0 2 2

2 2( , ) ( , )

4 4

BD CE AE CDx y

C AB C AB

2 2 1Ax By Cxy Dx Ey

2

arctan( 1 )B A B A

C C

1 2

( , ) ( , )a bJr Jr

where

2 21

2 22

1 ( ( ) ),

21

( ( ) ).2

r A B B A C

r A B B A C

Shape-based Detection (cont.)

center

orientation

axes

Shape-based Detection (cont.)

• Separation of inner and outer boundary– Based on distance to center of detected ellipse

from boundary pixels

Green = detected ellipse from boundary pixels. Red = inner boundary. Blue = outer boundary

99/006/093006

• Shape detection of inner and outer boundary. Shape-based Detection (cont.)

99/006/093006

99/006/070027 Green = RHT ellipses. Red = Inner. Blue= outer boundaries of the aurora arc.

More Experimental Results

96/344/233133 97/011/094246

99/006/21312397/010/150934

Experimental Configuration

• Machine:– CPU: 2.3 GHz– Memory: 512 MB– OS: Windows XP

• Run time (wall clock)– 3 MRHT runs each with 100,000 fittings

• One run for center estimation, two runs for inner and outer boundary detection

45 seconds for each image

Conclusion

• Shape-Based Fitting

– Goal: Better-Localizing Auroral Oval

– Upcoming:

• Couple w/ k-means (Hung and Germany, 2003)

• Longer Term:

– Auroral Classification

– Temporal Evolution Tracking