Final year computer science projects

1. Project topics and
concepts
Dr.S.Purushothaman & Dr.P.Rajeswari
Dr.S.Purushothaman & Dr.P.Rajeswari 1

2. List of final year BSc, BE projects for
Computer science(CS) and Computer science
and Engineering(CSE)
 3D Facial Modeling
 Wood Defect Recognition
 The Contourlet Based Image Recovery And Denoising
 Texture Segmentation Using Rotational Invariant Moment Technique
 Transmitter Placement Using Genetic Algorithm
 Surveillance Robot For Tracking Multiple Moving Targets Using Artificial Neural
Networks (ANN)
 Software Security Using Neural Networks
 Secure Transaction Using Steganography
 Steganalysis
 Segmentation Of Textures Using Gabor Filter
Dr.S.Purushothaman & Dr.P.Rajeswari 2

3. 3D Facial Modeling
This work focuses on 3D facial modeling using three images of a face. Each image
is taken at 90o.
Each image is segmented to identify skin, to locate eye centres, nose profile,
mouth profiles.
All the three images are combined to form a 3D facial model.
The segmented portions of the images are placed on a standard computer plastic
model.
Subsequently, the various features of the plastic model are animated
corresponding to the various positions of the features in the subsequent images.
Dr.S.Purushothaman & Dr.P.Rajeswari 3

4. Wood Defect Recognition
 The quality of a board or a sheet of veneer determines its
potential uses and the price for the saw mills.
 Automatic detection of the defects in the wood surface and
grading of the products is one of the key interest areas in
the mechanical wood industry.
 In this work, intelligent methods for knot recognition is
implemented using Self organizing map(SOM).
 Defective wood is used as template.
 During training of SOM, the SOM learns defective wood.
 During testing of the processed a test picture is given as
input that contains a combination of all defects
Dr.S.Purushothaman & Dr.P.Rajeswari 4

5. The Contourlet Based Image Recovery And
Denoising
The contourlet transform consists of two modules: the Laplacian Pyramid
and the Directional Filter Bank.
When both of them use perfect reconstruction filters, the contourlet
expansion and reconstruction is a Perfect dual.
Therefore, the contourlet transform can be employed as a coding scheme.
The contourlet coefficients derived above can be transmitted through the
wireless channel in the same way as transmitting the original image,
where the transmission is prone to noise and block loss.
However, the reconstruction at the receiver performs differently if the
image is transmitted directly or coded by the contourlet Transform.
The project studies the performance of the contourlet coding in image
recovery and denoising.
The simulation results show that for general images the contourlet
transform is quite competitive to the wavelet transform in the signal to
noise ration(SNR) sense and in visual effect.
Dr.S.Purushothaman & Dr.P.Rajeswari 5

6. Texture Segmentation Using Rotational
Invariant Moment Technique
Texture segmentation plays an important role in recognizing
and identifying a material, type of characteristic for
particular image.
Wavelets are employed for the computation of single and
multi-scale roughness features because of their ability to
extract information at different resolutions.
Features are extracted in multiple directions using
directional wavelet obtained from partial derivative of
Gaussian distribution function.
The first and second derivative wavelets are used to obtain
the features of the textured image at different orientations
like 0o , 45o , 90o and 135o and scales such as 1, 2 and 4.
Dr.S.Purushothaman & Dr.P.Rajeswari 6

7. ……continued
The feature extraction part consists of two stages, the
extraction of directional roughness feature and the
percentage of energy feature.
The directional roughness features results in high quality
texture segmentation performance, whereas the use of
percentage of energy feature retains the important properties
of fractal dimension based features like insensitivity to
absolute illumination and contrast.
The percentage energy feature computed using exponential
wavelets is used for segmenting different features in a given
image by using k-means algorithm.
For classification purpose database has been created from
different texture samples and classification is done using
template matching technique.
Dr.S.Purushothaman & Dr.P.Rajeswari 7

8. Transmitter Placement Using Genetic
Algorithm
 Wireless communication is part and parcel of modern
communication methods.
 Cell phones have become handy to everyone for instant
communication.
 During such communication, clarity, continuity and less noise
are the major parameters considered.
 To communicate between two or more cell phone users, a
transceiver should be erected, called base station.
 The base station depending upon quality, capacity will decide
the number of base stations in a given area.
 The base station is similar to a telephone exchange.
 What is the optimal number of base station required so that
they can communicate with their service providers called nodes
effectively without any redundancy or duplication or more
number of base stations than that is required to satisfy all
the service providers.
Dr.S.Purushothaman & Dr.P.Rajeswari 8

9. …….continued
The desire to make computers think, as human being do,
resulted in the development of Genetic algorithm.
Genetic algorithm is one of the artificial intelligent
methods which proves to be superior in many aspects when
compared to other classical methods in solving character
recognition problem.
The solution generated out of training the algorithm is
positive and definite.
Dr.S.Purushothaman & Dr.P.Rajeswari 9

10. Surveillance Robot For Tracking Multiple
Moving Targets Using Artificial Neural
Networks (ANN)
Object tracking is a challenging task in spite of all sophisticated methods that have
been developed.
The major challenge is to keep track of the object of a particular choice.
In this work, a new video moving object-tracking method is proposed.
The segmentation of the video is done by contextual clustering.
The features of the segmented image is further processed by the imfeature properties
of the matlab.
The imfeature provides 24 properties.
In this work, two important properties are used to process the features of the
segmented image for highlighting the presence of the human.
The co-ordinates of the human in the video are given as input for the Kalman filter.
This process is further repeated for the successive video frames.
An artificial neural network with supervised backpropagation algorithm learns the
input output scenarios of the Kalman filter and provides a better estimate of the
movement of the human in the video frame.
A multitarget human tracking is attempted.
Dr.S.Purushothaman & Dr.P.Rajeswari 10

11. Software Security Using Neural Networks
 This project involves the development of security for software.
 The project involves key generation and key recovery procedures.
 These two procedures avoid pirating any newly developed marketable
package.
 Key generation and key recovery software involves intelligent
techniques to create secured keys.
 These keys play an important role in providing access to the licensed
software.
 During generation of keys Expiry date, Version and Ethernet number of
the customer are taken into consideration and keys are developed.
 The keys are used as inputs to the artificial neural network.
 The outputs of artificial neural network are encoded as floating
values that plays important role in avoiding piracy.
 In addition, two sets of final weight files are developed.
 Altogether, four files along with the required software will be
provided to the customer by the vendor.
Dr.S.Purushothaman & Dr.P.Rajeswari 11

12. ….continued
The customer will install all the software in the computer.
During the execution of the software, the recovery program
will convert the floating-point values into characters that
are then reassembled to get Ethernet number and Expiry date.
Subsequently a separate program will access the system date
and existing Ethernet number.
Comparison between the obtained and the existing Ethernet
number is done.
If the strings are matching then a check is made if the
system date is less than expiry date of the original
software.
If everything matches then the execution of the software
continues.
Dr.S.Purushothaman & Dr.P.Rajeswari 12

13. Secure Transaction Using
Steganography
The work aims at incorporating a concept of hiding message
into another message.
The includes hiding image into image, text into image, text
into text, sound into sound and so on.
A preferred image is taken as a standard for hiding secret
images. Logic has been developed to hide message and unhide
the message.
The steganography is possible among people who have hiding
and unhiding message software.
In addition to standard hiding procedure in steganography,
different other combination of methods can be implemented.
In addition, cryptography can also be used.
Dr.S.Purushothaman & Dr.P.Rajeswari 13

14. Steganalysis
Sequential steganography as those class of embedding algorithms
that hide messages in consecutive (time, spatial or frequency
domain) features of a host signal.
The project presents a steganalysis method that estimates the
secret key used in sequential steganography.
A theory is developed for detecting abrupt jumps in the
statistics of the stego signal during steganalysis.
Stationary and non-stationary host signals with low, medium and
high SNR embedding are considered.
A locally most powerful steganalysis detector for the low SNR
case is also derived. Several techniques to make the
steganalysis algorithm work for non-stationary digital image
steganalysis are also presented.
Extensive experimental results are shown to illustrate the
strengths and weaknesses of the proposed steganalysis algorithm.
Dr.S.Purushothaman & Dr.P.Rajeswari 14

15. Segmentation Of Textures Using Gabor
Filter
The work involves segmenting textured images used in textile industries.
Many conventional algorithms are available for segmentation but Gabor
segmentation is used.
Gabor filter is a set of filter banks obtained at different orientation
corresponding to the size of actual image texture.
Each filter bank is convolved with the actual image to obtain features of
the image.
The features obtained are almost same when different Gabor filters are
convolved with the original image.
In order to make sure that the convolved image has the correct features,
all the convolved matrices are averaged.
The averages matrix is assigned class label based on the range of values
predefined.
The class label is in the form of alphabets.
When the labeled matrix is viewed, it shows the segmented portion of the
image.
Subsequently, kronecker delta rule is applied to refine the segmentation
process.
Dr.S.Purushothaman & Dr.P.Rajeswari 15

16. ….continued
The nature of the project involves in taking an image texture
as input and getting the partitioned or segmented textures as
output.
It can be very well justified in doing this project as
automatic segmentation, identification and classification
plays an important role in image processing.
The future of the project is unlimited.
There is lot of demand in segmentation of 3D objects,
especially in magnetic resonance imaging, computer
tomography.
Dr.S.Purushothaman & Dr.P.Rajeswari 16

17.  Thank you
 Contact dr.s.purushothamann@gmail.com for further clarifications
Dr.S.Purushothaman 17