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We were able to successfully locate the license plate in about 70% of our sample pictures, and of the characters we extracted, we were able to recognize them with about 72.7% accuracy (619 sets of training data).

Future improvements

Compression and cropping

Since we were targeting Texas plates, which only have red, blue, and white colors, we were able to black out many parts of the images by wiping out all green regions. In the future, however, we would like to be able to recognize plates not from Texas that might have green components. Therefore, we should find a criteria for finding the plates other than color.

Letter recognition

Acquiring state pattern and convention attributes

In many license plates, it is difficult to tell the difference between a zero and an O, even for a human. Therefore, for the purposes of this project, zeros and Os were considered the same. However, in many states, it is actually possible to tell the difference because the license plate has a set pattern (e.g., 2 letters, 2 numbers, 2 letters). In the future, we could identify what state the plate comes from and then make use of this knowledge to get more accuracy in letter recognition.

Multi-class support vector machine

In addition, one of the characteristics of SVM is that is solves a two-class problem. In order to get around this, for our project, we used a one-against-the-rest approach. This meant that we basically used the SVM machine to answer the question, "Is this a __?" 35 (A-Z, 1-9) times for each unknown letter/digit. In the future, we will want to look at more efficient and accurate methods. One of the possible improvement can be found in the work by T.-K. Huang, R. C. Weng, and C.-J. Lin. Generalized Bradley-Terry Models and Multi-class Probability Estimates. Journal of Machine Learning Research

Automated training set generation and extraction efficiency

Finally, currently, any digit that we feed into the SVM will register as something; we have no way of telling whether the image is in fact a letter/digit. In the future, we would like to train the machine to be able to tell characters from non-characters. This will allow less rigorous (and time-consuming) computation in the image-processing section and give our algorithm greater flexibility.


Chih-Chung Chang and Chih-Jen Lin, LIBSVM : a library for support vector machines, 2001. Software available at (External Link)

Special thanks

    Thanks to:

  • Dr. Aswin Sankaranarayanan, our mentor
  • Dr. Richard Baraniuk, the ELEC 301 instructor
  • Dr. Fatih Porikli (MERL), for providing us with a license plate dataset
  • Drew Bryant and Brian Bue for technical advising

Questions & Answers

how do they get the third part x = (32)5/4
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I got X =-6
ok. so take the square root of both sides, now you have plus or minus the square root of 20= x-6
oops. ignore that.
so you not have an equal sign anywhere in the original equation?
Commplementary angles
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algebra 2 Inequalities:If equation 2 = 0 it is an open set?
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or infinite solutions?
The answer is neither. The function, 2 = 0 cannot exist. Hence, the function is undefined.
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rolling four fair dice and getting an even number an all four dice
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Differences Between Laspeyres and Paasche Indices
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No. 7x -4y is simplified from 4x + (3y + 3x) -7y
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. After 3 months on a diet, Lisa had lost 12% of her original weight. She lost 21 pounds. What was Lisa's original weight?
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Yes, Nanotechnology has a very fast field of applications and their is always something new to do with it...
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good afternoon madam
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In this morden time nanotechnology used in many field . 1-Electronics-manufacturad IC ,RAM,MRAM,solar panel etc 2-Helth and Medical-Nanomedicine,Drug Dilivery for cancer treatment etc 3- Atomobile -MEMS, Coating on car etc. and may other field for details you can check at Google
anybody can imagine what will be happen after 100 years from now in nano tech world
after 100 year this will be not nanotechnology maybe this technology name will be change . maybe aftet 100 year . we work on electron lable practically about its properties and behaviour by the different instruments
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silver nanoparticles could handle the job?
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Prasenjit Reply
At high concentrations (>0.01 M), the relation between absorptivity coefficient and absorbance is no longer linear. This is due to the electrostatic interactions between the quantum dots in close proximity. If the concentration of the solution is high, another effect that is seen is the scattering of light from the large number of quantum dots. This assumption only works at low concentrations of the analyte. Presence of stray light.
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the Beer law works very well for dilute solutions but fails for very high concentrations. why?
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Source:  OpenStax, Elec 301 group project- license plate extraction (lipe). OpenStax CNX. Dec 16, 2009 Download for free at http://cnx.org/content/col11145/1.2
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