Advisor Name (Neamat S. Abdel Kader)
Project #1:
Mobile-based Visual Localization Aid for the Blind
This is a computer vision based project that aims to help a blind person find her/his location
in indoor environment. The blind person is equipped with a mobile phone that consists of a
camera, a speaker as well as the stand alone localization application. The map of the indoor
environments is described by a set of images. The localization is performed by extracting a
feature from the image of the unknown location and comparing it the features of the
environment. The feature which has the nearest distance to that of the novel image is
considered and a voice massage is sent the blind person with the location information. Color
histogram is proposed as the image feature.
The project developed using C++ and Symbian OS or Java.
Project #2:
Image compression
and
telecommunication applications such as teleconferencing, digital broadcast codec and video
technology, etc. Although storage media is becoming cheaper, the requirement for compressed
images still holds for communication through limited capacity networks, or for storage on
pervasive computing devices with limited storage such as hand held devices. The fundamental
goal of image compression is to reduce the bit rate for transmission or storage while maintaining
an acceptable fidelity or image quality. One of the most successful applications of wavelet
methods is transform-based image compression (also called coding). The overlapping nature of
the wavelet transform alleviates blocking artifacts, while the multiresolution character of the
wavelet decomposition leads to superior energy compaction and perceptual quality of the
decompressed image.
Image compression is a key technology in the development of various multimedia computer services
. Number of Students (4-5 suggested)
Project #3:
Speech Recognition for Deaf Persons.
Construct a speech recognition system using database consisting of about 150 isolated words
common for deaf persons to help them to use computers. The speech corpus will be divided in
separate classes according to some levels. The recognition will be transferred from one level to
another one. The recognized word appears as a sign familiar to the deaf person. The recognition
system can be based on Vector quantization (VQ), dynamic time warpping (DTW), or hidden
Markov model (HMM). The system can in the another direction accept a sign from a deaf
person, then using image recognition to give the corresponding speech of the sign.
. Number of Students (4-5 suggested)
Project #4:
.
Security System based on Face Recognition.
. Biometric systems are used to identify or verify human beings through their behavioral and
physical characteristics. Face is one of the most significant features at all for other biometrics.
We aim to use powerful techniques to extract face features to distinguish persons with high
performance.
A codevector referred (or matched) count histogram, which is obtained by vector quantization
(VQ) processing of the facial image, is utilized as a very effective personal feature. By applying
appropriate low pass filtering and VQ processing to a facial image, useful features for face
recognition can be extracted. The wavelet transform coefficients can be also used for feature
extraction, which produces the feature components in a low dimensional subspace of an image,
even under moderate variation in lighting and facial expression.
A neural network (NN) based algorithm will be applied for face recognition, which is insensitive
to variation of lighting and facial expression.
. Number of Students (4-5 suggested)
Project #5:
A Multimedia Software Tool for Speech Coder Design
Multimedia teaching tools have been widely used in many universities to help students
understand abstract concepts and theories. This project aims to add some new features to
a Windows-based multimedia learning tool to help students learn the concepts of speech
coding. The software tool should allow users to change the parameters of speech coders
through user interface controls. Visual C++ and Microsoft Foundation Class (MFC)
libraries will be used in this project. The current version of the software can be found in
http://www.en.polyu.edu.hk/~mwmak/Download.htm.
Pre-requisite: C/C++, Visual C++, and DSP
Knowledge and skills to be learnt: Speech coding techniques, Microsoft MFC, multithreading programming, and audio programming.
Project #6:
Speech Coding Applied On Wireless Channels
Speech coding is the process of obtaining a compact representation of voice signals for efficient
transmission over band-limited wired and wireless channels and/or storage. Today, speech
coders have become essential components in telecommunications and in the multimedia
infrastructure. Commercial systems that rely on efficient speech coding include cellular
communication, voice over internet protocol (VOIP), videoconferencing, electronic toys,
archiving, and digital simultaneous voice and data (DSVD), as well as numerous PC-based
games and multimedia applications. A speech coder converts a digitized speech signal into a
coded representation, which is usually transmitted in frames. A speech decoder receives coded
frames and synthesizes reconstructed speech.
. The performance of the speech coder determines the quality of the recovered speech and the
storage of the system. In wireless communication systems, bandwidth is a precious commodity,
and service provides are continuously met with the challenge of accommodating more users
within a limited allocated bandwidth. Low bit rate speech coding offers a way to meet this
challenge. The lower the bit-rate, the more speech channels can be compressed within a given
bandwidth. A number of techniques were developed and standardized as speech coding
algorithms. The Mixed Excitation Linear Prediction (MELP) is a low bit rate coding technique
developed originally for wireless communication.