International Journal of Electrical and Computer Engineering (IJECE), 2017
Automatic Number Plate Recognition (ANPR) is an intelligent system which has the capability to re... more Automatic Number Plate Recognition (ANPR) is an intelligent system which has the capability to recognize the character on vehicle number plate. Previous researches implemented ANPR system on personal computer (PC) with high resolution camera and high computational capability. On the other hand, not many researches have been conducted on the design and implementation of ANPR in smartphone platforms which has limited camera resolution and processing speed. In this paper, various steps to optimize ANPR, including pre-processing, segmentation, and optical character recognition (OCR) using artificial neural network (ANN) and template matching, were described. The proposed ANPR algorithm was based on Tesseract and Leptonica libraries. For comparison purpose, the template matching based OCR will be compared to ANN based OCR. Performance of the proposed algorithm was evaluated on the developed Malaysian number plates’ image database captured by smartphone’s camera. Results showed that the a...
Abstract Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sp... more Abstract Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals, ie speech signal. Compressive sensing is a new paradigm of acquiring signals, fundamentally different from uniform rate digitization followed by compression, often used for transmission or storage. In this paper, a novel algorithm for speech coding utilizing CS principle is developed. The sparsity of speech signals is exploited using gammatone filterbank and Discrete Cosine Transform (DCT) in ...
ABSTRACT Hybrid electric vehicles (HEVs) powered by electric machines and an internal combustion ... more ABSTRACT Hybrid electric vehicles (HEVs) powered by electric machines and an internal combustion engine (ICE) are a promising mean of reducing emissions and fuel consumption without compromising vehicle functionality and driving performances. This paper presents the design of an environmental friendly hybrid car that feature the gasoline engine and batteries pack. The fuel consumption benefited by hybridization are benchmarked to conventional Gasoline and Diesel fueled vehicles. The relationship between fuel consumption and vehicle weight is investigated for Gasoline as well as for Diesel fueled vehicles. Although the automobile manufacturers have reduced the greenhouse gases such as hydro-carbons, carbon monoxide, carbon dioxide, etc., from the vehicle, they cannot produce a zero-emission vehicle unless they produce an electric vehicle (EV). An electric vehicle is an emission free, environmental friendly vehicle. The proposed design of HEV intelligently gets around the individual problems associated with the gasoline engine and the electric vehicle. It diminishes the production of emissions and the use of fuel. The problem of batteries for the electric vehicle is conquered. An HEV charges itself; it never has to be plugged in. When it does not provide power, the motor can run as a generator to transfer energy from regenerative braking and from the gasoline engine to the batteries.
Abstract Stenography systems has too many approaches , it has a lot of applications and differe... more Abstract Stenography systems has too many approaches , it has a lot of applications and different ways, too many type of attackers have been tried to attacked the information that already embed in the carrier, however there is not yet a real stego-analysis system offered, the goal of ...
... Conclusion: We present a novel signal boosting technique for the gene and exon prediction. ..... more ... Conclusion: We present a novel signal boosting technique for the gene and exon prediction. ... In particular, a relative improvement of more than 3 to 15% was achieved over the DFT spectral content, anti-notch and multi-stage filtering approaches. ...
High processing time is required to classify genomic sequences and to identify protein coding of ... more High processing time is required to classify genomic sequences and to identify protein coding of a DNA sequence. While computer performance has been driven largely by decreasing the size of chips while increasing the number of transistors they contain, the current computing trend is multicore system in which two or more independent cores are integrated into a single package. This paper presents the parallel implementation of the gene and exon identification of DNA sequences using the previously developed modified Gabor wavelet transform on multicore systems. Single Program Multiple Data (SPMD) parallel paradigm will be used in the parallel implementation. Furthermore, the efficiency of the proposed algorithm will be analyzed using Amdahl's law.
The availability of inexpensive PC sound cards that can simultaneously play and record stereo dig... more The availability of inexpensive PC sound cards that can simultaneously play and record stereo digital audio files permits a single PC or laptop or netbook to function as both a signal generator and as a dual-channel recording digital oscilloscope. This paper presents how sound card with Matlab Data Acquisition Toolbox can be utilized for instrumentation and control. The buffer hardware circuit or signal conditioning circuit is developed and implemented to enable sound card to be functioned like oscilloscope. Preliminary results showed that sound card with the developed software has a good potential for instrumentation and control.
In the past few years, cluster computing has been accepted widely as parallel platform because of... more In the past few years, cluster computing has been accepted widely as parallel platform because of its high performance at an affordable cost. To maximize the use of available resources, resource monitoring for cluster computing is required. The resource information collected can be used by any parallel applications, i.e. parallel motion estimation, for handling variation of available resources in typical time-sharing computers. Therefore, the computing load can be distributed properly among n processors. In this paper, we present the development of resource monitoring for cluster computing using MPI programming model to achieve efficient parallel motion estimation. Results show the effectiveness of our method in which the faster parallel execution time can be achieved.
Symmetric Multiprocessor (SMP) system and cluster of SMPs have become widely available as cost-ef... more Symmetric Multiprocessor (SMP) system and cluster of SMPs have become widely available as cost-effective parallel platforms. In this paper, the comparison of Motion Estimation (ME) algorithms implemented on SMP system and cluster of SMPs was evaluated. The same parallel program written using MPI (Message-Passing Interface) programming model with different compilation procedures were implemented. Results show that the parallel ME algorithms scales well for SMP system (up to 6 processors) and cluster of SMPs (up to 23 processors). In terms of price/performance ratio, it is preferable to have a node with dual-processors than single-processor.
In recent years, cluster computing has been accepted widely as a parallel platform because of its... more In recent years, cluster computing has been accepted widely as a parallel platform because of its high performance at an affordable cost. To make the best use of the cluster computing resources, a resource monitoring program is needed. The information collected can be used by any parallel application, i.e. parallel motion estimation, for handling load variation in typical time-sharing computers. Therefore, the parallel workload can be distributed properly among n processors. In this paper, we present the development of resource monitoring for cluster computing using the MPI programming model and its application to parallel motion estimation. Results show the effectiveness of our method in which a faster parallel execution time can be achieved.
This paper presents a comparison of three auditory temporal masking models for speech and audio c... more This paper presents a comparison of three auditory temporal masking models for speech and audio coding applications. The first model was developed based upon the existing forward masking psychoacoustic data with an assumption of an approximately 200 ms. The model’s dynamic parameters were derived from this data. The previously developed second model was based upon the principle of an exponential
Abstract Forward masking models have been used successfully in speech enhancement and audio codin... more Abstract Forward masking models have been used successfully in speech enhancement and audio coding. Currently, simple forward masking models have been employed to predict the forward masking threshold. In this paper, an accurate approximation of forward masking threshold using neural networks is proposed. A performance comparison to the other existing masking models in speech enhancement application is presented. Objective measures using PESQ demonstrates that our proposed forward masking model, provides ...
The scalable video coding extension of H.264/AVC is a current standardization project. This paper... more The scalable video coding extension of H.264/AVC is a current standardization project. This paper deals with encoding process of the Fine-Grain SNR Scalability (FGS) scheme with two enhancement layers for enhancing the streaming video quality over wireless LAN. The scalable video coding algorithm has been implemented and simulated with various parameters in various wireless LAN conditions. The simulation results showed that the proposed algorithm is suitable for wireless LAN channel capacity.
The scalable video coding H.264/SVC is the video coding standard which is an extension of H.264/A... more The scalable video coding H.264/SVC is the video coding standard which is an extension of H.264/AVC. Because of its scalability, H.264/SVC has gained a great interest in video transmission. Partial bit stream can be transmitted and decoded by the H.264/SVC in order to provide quality in lower temporal or spatial resolutions or reduced fidelity while retaining a reconstruction quality that is high relative to the rate of the partial bit streams. Hence, H.264/SVC provides functionalities such as graceful degradation in lossy transmission environments, i.e. wireless networks, as well as bit rate format, and power adaptation. This paper deals with the Medium-Grain SNR Scalability (MGS) scheme and fast coding mode decision. The MGS scheme with two enhancement layers is applied for enhancing the streaming video quality. To perform an optimum mode decision, motion estimation is performed for all Macro Block (MB) modes, and the Rate Distortion (RD) costs are compared to identify an MB mode with the smallest RD cost. This increases computational complexity of H.264/SVC encoding. Therefore, fast mode decision algorithm scheme was implemented to speed up the encoding time. From the experiment, the fast mode decision was able to decrease the encoding process up to 30.22%.
Many attempts to accurately classify speech and music have been investigated over the years. This... more Many attempts to accurately classify speech and music have been investigated over the years. This paper presents modulation features for effective speech and music classification. A Gammatone filter bank is used as a front-end for this classification system, where amplitude modulation (AM) and frequency modulation (FM) features are extracted from the critical band outputs of the Gammatone filters. In addition, the cepstral coefficients are also calculated from the energies of the filter bank outputs. The cepstral coefficients, AM and FM components are all given as input feature vector to Gaussian mixture models (GMM) which act as a speech-music classifier. The output probabilities of all GMMs are combined before making a decision. The error rate for different types of music has also been compared. Low frequency musical instruments such as the electric bass guitar were found to be more difficult to discriminate from speech; however, the proposed features were able to reduce such errors significantly
International Journal of Electrical and Computer Engineering (IJECE), 2017
Automatic Number Plate Recognition (ANPR) is an intelligent system which has the capability to re... more Automatic Number Plate Recognition (ANPR) is an intelligent system which has the capability to recognize the character on vehicle number plate. Previous researches implemented ANPR system on personal computer (PC) with high resolution camera and high computational capability. On the other hand, not many researches have been conducted on the design and implementation of ANPR in smartphone platforms which has limited camera resolution and processing speed. In this paper, various steps to optimize ANPR, including pre-processing, segmentation, and optical character recognition (OCR) using artificial neural network (ANN) and template matching, were described. The proposed ANPR algorithm was based on Tesseract and Leptonica libraries. For comparison purpose, the template matching based OCR will be compared to ANN based OCR. Performance of the proposed algorithm was evaluated on the developed Malaysian number plates’ image database captured by smartphone’s camera. Results showed that the a...
Abstract Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sp... more Abstract Compressive sensing (CS) is a new approach to simultaneous sensing and compression of sparse and compressible signals, ie speech signal. Compressive sensing is a new paradigm of acquiring signals, fundamentally different from uniform rate digitization followed by compression, often used for transmission or storage. In this paper, a novel algorithm for speech coding utilizing CS principle is developed. The sparsity of speech signals is exploited using gammatone filterbank and Discrete Cosine Transform (DCT) in ...
ABSTRACT Hybrid electric vehicles (HEVs) powered by electric machines and an internal combustion ... more ABSTRACT Hybrid electric vehicles (HEVs) powered by electric machines and an internal combustion engine (ICE) are a promising mean of reducing emissions and fuel consumption without compromising vehicle functionality and driving performances. This paper presents the design of an environmental friendly hybrid car that feature the gasoline engine and batteries pack. The fuel consumption benefited by hybridization are benchmarked to conventional Gasoline and Diesel fueled vehicles. The relationship between fuel consumption and vehicle weight is investigated for Gasoline as well as for Diesel fueled vehicles. Although the automobile manufacturers have reduced the greenhouse gases such as hydro-carbons, carbon monoxide, carbon dioxide, etc., from the vehicle, they cannot produce a zero-emission vehicle unless they produce an electric vehicle (EV). An electric vehicle is an emission free, environmental friendly vehicle. The proposed design of HEV intelligently gets around the individual problems associated with the gasoline engine and the electric vehicle. It diminishes the production of emissions and the use of fuel. The problem of batteries for the electric vehicle is conquered. An HEV charges itself; it never has to be plugged in. When it does not provide power, the motor can run as a generator to transfer energy from regenerative braking and from the gasoline engine to the batteries.
Abstract Stenography systems has too many approaches , it has a lot of applications and differe... more Abstract Stenography systems has too many approaches , it has a lot of applications and different ways, too many type of attackers have been tried to attacked the information that already embed in the carrier, however there is not yet a real stego-analysis system offered, the goal of ...
... Conclusion: We present a novel signal boosting technique for the gene and exon prediction. ..... more ... Conclusion: We present a novel signal boosting technique for the gene and exon prediction. ... In particular, a relative improvement of more than 3 to 15% was achieved over the DFT spectral content, anti-notch and multi-stage filtering approaches. ...
High processing time is required to classify genomic sequences and to identify protein coding of ... more High processing time is required to classify genomic sequences and to identify protein coding of a DNA sequence. While computer performance has been driven largely by decreasing the size of chips while increasing the number of transistors they contain, the current computing trend is multicore system in which two or more independent cores are integrated into a single package. This paper presents the parallel implementation of the gene and exon identification of DNA sequences using the previously developed modified Gabor wavelet transform on multicore systems. Single Program Multiple Data (SPMD) parallel paradigm will be used in the parallel implementation. Furthermore, the efficiency of the proposed algorithm will be analyzed using Amdahl's law.
The availability of inexpensive PC sound cards that can simultaneously play and record stereo dig... more The availability of inexpensive PC sound cards that can simultaneously play and record stereo digital audio files permits a single PC or laptop or netbook to function as both a signal generator and as a dual-channel recording digital oscilloscope. This paper presents how sound card with Matlab Data Acquisition Toolbox can be utilized for instrumentation and control. The buffer hardware circuit or signal conditioning circuit is developed and implemented to enable sound card to be functioned like oscilloscope. Preliminary results showed that sound card with the developed software has a good potential for instrumentation and control.
In the past few years, cluster computing has been accepted widely as parallel platform because of... more In the past few years, cluster computing has been accepted widely as parallel platform because of its high performance at an affordable cost. To maximize the use of available resources, resource monitoring for cluster computing is required. The resource information collected can be used by any parallel applications, i.e. parallel motion estimation, for handling variation of available resources in typical time-sharing computers. Therefore, the computing load can be distributed properly among n processors. In this paper, we present the development of resource monitoring for cluster computing using MPI programming model to achieve efficient parallel motion estimation. Results show the effectiveness of our method in which the faster parallel execution time can be achieved.
Symmetric Multiprocessor (SMP) system and cluster of SMPs have become widely available as cost-ef... more Symmetric Multiprocessor (SMP) system and cluster of SMPs have become widely available as cost-effective parallel platforms. In this paper, the comparison of Motion Estimation (ME) algorithms implemented on SMP system and cluster of SMPs was evaluated. The same parallel program written using MPI (Message-Passing Interface) programming model with different compilation procedures were implemented. Results show that the parallel ME algorithms scales well for SMP system (up to 6 processors) and cluster of SMPs (up to 23 processors). In terms of price/performance ratio, it is preferable to have a node with dual-processors than single-processor.
In recent years, cluster computing has been accepted widely as a parallel platform because of its... more In recent years, cluster computing has been accepted widely as a parallel platform because of its high performance at an affordable cost. To make the best use of the cluster computing resources, a resource monitoring program is needed. The information collected can be used by any parallel application, i.e. parallel motion estimation, for handling load variation in typical time-sharing computers. Therefore, the parallel workload can be distributed properly among n processors. In this paper, we present the development of resource monitoring for cluster computing using the MPI programming model and its application to parallel motion estimation. Results show the effectiveness of our method in which a faster parallel execution time can be achieved.
This paper presents a comparison of three auditory temporal masking models for speech and audio c... more This paper presents a comparison of three auditory temporal masking models for speech and audio coding applications. The first model was developed based upon the existing forward masking psychoacoustic data with an assumption of an approximately 200 ms. The model’s dynamic parameters were derived from this data. The previously developed second model was based upon the principle of an exponential
Abstract Forward masking models have been used successfully in speech enhancement and audio codin... more Abstract Forward masking models have been used successfully in speech enhancement and audio coding. Currently, simple forward masking models have been employed to predict the forward masking threshold. In this paper, an accurate approximation of forward masking threshold using neural networks is proposed. A performance comparison to the other existing masking models in speech enhancement application is presented. Objective measures using PESQ demonstrates that our proposed forward masking model, provides ...
The scalable video coding extension of H.264/AVC is a current standardization project. This paper... more The scalable video coding extension of H.264/AVC is a current standardization project. This paper deals with encoding process of the Fine-Grain SNR Scalability (FGS) scheme with two enhancement layers for enhancing the streaming video quality over wireless LAN. The scalable video coding algorithm has been implemented and simulated with various parameters in various wireless LAN conditions. The simulation results showed that the proposed algorithm is suitable for wireless LAN channel capacity.
The scalable video coding H.264/SVC is the video coding standard which is an extension of H.264/A... more The scalable video coding H.264/SVC is the video coding standard which is an extension of H.264/AVC. Because of its scalability, H.264/SVC has gained a great interest in video transmission. Partial bit stream can be transmitted and decoded by the H.264/SVC in order to provide quality in lower temporal or spatial resolutions or reduced fidelity while retaining a reconstruction quality that is high relative to the rate of the partial bit streams. Hence, H.264/SVC provides functionalities such as graceful degradation in lossy transmission environments, i.e. wireless networks, as well as bit rate format, and power adaptation. This paper deals with the Medium-Grain SNR Scalability (MGS) scheme and fast coding mode decision. The MGS scheme with two enhancement layers is applied for enhancing the streaming video quality. To perform an optimum mode decision, motion estimation is performed for all Macro Block (MB) modes, and the Rate Distortion (RD) costs are compared to identify an MB mode with the smallest RD cost. This increases computational complexity of H.264/SVC encoding. Therefore, fast mode decision algorithm scheme was implemented to speed up the encoding time. From the experiment, the fast mode decision was able to decrease the encoding process up to 30.22%.
Many attempts to accurately classify speech and music have been investigated over the years. This... more Many attempts to accurately classify speech and music have been investigated over the years. This paper presents modulation features for effective speech and music classification. A Gammatone filter bank is used as a front-end for this classification system, where amplitude modulation (AM) and frequency modulation (FM) features are extracted from the critical band outputs of the Gammatone filters. In addition, the cepstral coefficients are also calculated from the energies of the filter bank outputs. The cepstral coefficients, AM and FM components are all given as input feature vector to Gaussian mixture models (GMM) which act as a speech-music classifier. The output probabilities of all GMMs are combined before making a decision. The error rate for different types of music has also been compared. Low frequency musical instruments such as the electric bass guitar were found to be more difficult to discriminate from speech; however, the proposed features were able to reduce such errors significantly
Uploads