An automated DNA strands detection system featuring 32-bit ARM7TDMI microcontroller and VGA-CMOS digital image sensor
Loading...
Date
2009-03
Authors
Mohd Noor, Mohd Halim
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Genetic DNA recognition is a routine experiment for detecting the origin of
the species. Electrophoresis is one of the processes for such detection which has been
used extensively. One popular technique based on electrophoresis is agarose gel
sequencing. This method separates DNA molecules by size and eventually produces
high resolution DNA strands. It is achieved by moving the negatively charged
molecules through an agarose matrix towards cathode and anode if the molecules are
positively charged. Manual analysis on the agarose gel image, usually is time
consuming and prone to human errors. Automated agarose gel image analYSIS
nullifies the problems and speed up the process. Hence the objective of this project is
to develop an imaging system for automated DNA strands detection. This project can
be divided into two stages. The first stage is the development of an imaging system
that is able to capture agarose gel electrophoresis images. An electronic circuit is
designed to interface and control two main components of the imaging system which
are CMOS image sensor and microcontroller. The design is focused on developing a
memory system that can temporarily store the image data before it is used for image
processing. The imaging system was tested on a real electrophoresis application. The
system is successfully able to capture agarose gel electrophoresis image of size
320 x 240 of 10-bit length. It was observed that the images were heavily corrupted
with noise inherently present in the imaging system. The second stage is the
development of image processing algorithms and pattern recognition software. The
DNA detection algorithm adopts image subtraction technique to establish DNA
recognition. For simplicity the algorithms are implemented in MATLABĀ®
environment. The image comparison algorithm is based on image subtraction
technique. The reference image is subtracted with the sample image and the
maximum intensity value and average of intensity value of the resultant image are
determined. The values are compared against the threshold values to establish
recognition. Twenty samples of five types of DNA have been used to evaluate the
accuracy and fidelity of the proposed procedures and methods. It was found that the
system is able to classify DNA strands with 98.16% of average accuracy rate.
Description
Keywords
Genetic DNA recognition is a routine experiment , for detecting the origin of the species