Constellation IdentificationAkinsanmi A.BBandhana Arti

The Night Sky People have watched the night skies for thousands of years.

Some just out of curiosity. Some out of boredom.

They noticed that there was a pattern in the way the stars revolved around the heavens. These patterns were grouped to form constellations.

has been useful in navigation before technology and even now.

Timing of agricultural seasons…

Astronomers label stars within a constellation based on their apparent brightness

88 constellations are recognized, 30 belonging to the northern hemisphere.

E.g. Orion (the great hunter).

Its difficult to notice this patternIf one is not familiar with them

So……..3

Objectives To identify constellations in pictures taken by

amateur cameras and perhaps beyond.

By using image processing techniques to recognize star patterns. Create database of Northern constellation compare with test images Select match

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Build Constellation database

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• Take constellation templates

Image credit: The constellations. International Astronomical Union

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Convert to binary With only stars Label according to

area(magnitude) Extract center and

area of each star (Regionprops)

Calculate distance of each star to star 1.

Set imaginary between 2 brightest stars as reference line

From star 1, calculate angle of other stars to this line.

Normalize values by distance to the 1st star

Combine these d1,d2, α1 ,m into a cell structure which represents a descriptor for that constellation.

Do this for all constellations, save in database

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Constellation database

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Test Image processing

Using threshold (T)

Removing stars less than area (a)

Test image courtesy:David Malin Binary

These values control the amount of stars in the Binary

Detection

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With descriptor (d1, d2, α1) for each extracted from binary image, find match in database with 10% error margin.

If half the total number of stars in constellation is found, the constellation has been detected

T=0.7,a=5

• Star brightness are not directly consistent with what template indicates.

• Presence of planet or unidentified bright objects.

• Time frame to make complete algorithm

• Different quality of test-images

Challenges

Future work

• Complete the algorithm to plot the detected constellation.

• Search for all constellations in a wide field image.

• The implemented methodology in this algorithm makes use of a combination of trivial functions and mathematical tools to achieve the identification of constellations.

• It was able to achieve good match for 25 of the 30 contellations using 50 test images.

Conclusion

Ursa major and minor Constellation