Week 11 ( 2. April. 2012 )

Assalamualaikum

Title of Activity :
- Study for experimental result.

Objective :
- To tested the proposed systems whether the systems is going fine or not.

Content / Procedure
- Test and simulate all the car plates taken and the percentage of successful experiments in the systems.
- Study of factors that makes the systems does not function properly.
- A set of 50 images were taken from :

a) Complex scene, in which several objects with complex textures are presented.
b) Various environment ( street, roadside and parking lot ).
c) Different inclined angles and distances relative to camera.

 - Different angles -

- Distance from the camera - 

- Car plate size - 

- A shiny surface -

- The fracture surface -

Result / Analysis :

- Performance for individual system subsection were as follows : 92.1 % of plates were located successfully, 85% characters were segmented correctly, 50 % of characters manually extracted plates and 93.2 % of these characters were correctly classified.

- The major factors of errors was mainly due to bad quality of input image during the acquisition stage.

Week 9 - 10 ( 22. March. 2012 )

Assalamualaikum...

Title of Activity :
- Recognizing license plate characters.

Objective :
- To identified and to finalize the results are ASCII character and numbers of the plate.
- To get a similar result like a segmentation process.
- To ensure which the architecture of a neural network want to be used.

Content / Procedure :
- Used a Multi Layer Perceptron Network trained with the back propagation algorithm.
- During learning process, characters of the constituted database are successively presented at the input layer of Multi Layer Perceptron Network and their corresponding outputs are compared to the desire output.
- Implementing Multi Layer Perceptron Network with two hidden layers of 35 and 10 neurons as neural network.
- I use 30 data on the pictures. 20 of them were used for training and last 12 were used for simulating and testing.
- The training data will get from Image Processing for the neural network is based on input training.bmp image which has exactly 36 characters ( 25 alphabets 10 numbers ). Every type of character is train automatically once we simulate the program.

Result / Analysis :

 ~ Neural Network Training Tool ~

- There are some problems when using fan beam transforms method, the systems cannot recognize the plate numbers.

- Fan beam transform method -

- Change from Fan beam transform method to other character recognition method. The result will get same, but must to train the alphabet and number more frequently.

- The most challenging part is about need to change the source code to suitable method many times.