In this paper, we propose digital image watermarking algorithm in the multiwavelet transform doma... more In this paper, we propose digital image watermarking algorithm in the multiwavelet transform domain. The embedding technique is based on the quantization index modulation technique and this technique does not require the original image in the watermark extraction. We have developed an optimization technique using the genetic algorithms to search for optimal quantization steps to improve the quality of watermarked image and robustness of the watermark. In addition, we analyze the performance of the proposed algorithm in terms of peak signal to noise ratio and normalized correlation. The experimental results show that our proposed method can improve the quality of the watermarked image and give more robustness of the watermark as compared to previous works.
Intrinsic images, including reflectance and illumination images, are desirable to many vision app... more Intrinsic images, including reflectance and illumination images, are desirable to many vision applications. An improved method for extracting intrinsic images from a single color image with integrated measures is presented. To start with, the input image convolves with a predefined set of derivative filters. The pixels of filtered images are then classified into reflectance-related or illumination-related using a criterion measure comprising three measures of filtered pixels calculated from the input image. The three measures are denoted as chromatic measure, blur measure, and intensity measure. Finally, the intrinsic images of the input image can be computed from the classification results of the filtered images. Both synthetic and real images have been utilized in our experiments. The results demonstrated that the proposed technique can effectively extract the intrinsic images from a single image.
2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2001
This paper proposes a method to obtain optimal 2 nd -order approximation preserving prefilters fo... more This paper proposes a method to obtain optimal 2 nd -order approximation preserving prefilters for a given orthogonal unbalanced multiwavelet basis. This procedure uses the prefilter construction introduced in [3]. The prefilter optimization scheme exploits the Taylor series expansion of the prefilter combined with the multiwavelet. Using the DGHM multiwavelet with the obtained optimal prefilter, we find that quadratic input signals are annihilated by the high-pass portion of filter bank at the first level of decomposition.
2006 1st International Symposium on Wireless Pervasive Computing, 2006
In this paper, we present an algorithm for robust audio watermarking in wavelet transform domain.... more In this paper, we present an algorithm for robust audio watermarking in wavelet transform domain. Using Daubechies wavelet decomposition, we perform watermark embedding to wavelet coefficients of host audio signal. In enhance security, a pseudo-random permutation is performed to disperse the spatial relationship of the binary watermark image. In our watermark embedding algorithm, we search for the optimal intensity of
Proceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, 2004. ISPACS 2004., 2004
The objective of this paper is to present a new method for automatically detecting, localizing an... more The objective of this paper is to present a new method for automatically detecting, localizing and classifying various types of power quality disturbances. The new method is based on wavelet transform analysis, artificial neural networks, and the mathematical theory of evidence. The proposed detection and localization algorithm is carried out in the wavelet transform domain using multiresolution signal decomposition techniques and the proposed classification method is carried out in the sets of multiple neural networks using a learning vector quantization network. The outcomes of the networks are then integrated using a voting decision making scheme. The performance of the automatic detection and localization have 90.14% accuracy and the error is less than 5%.
TENCON 2005 - 2005 IEEE Region 10 Conference, 2005
This paper proposes a wavelet-based neural network classifier for recognizing power quality distu... more This paper proposes a wavelet-based neural network classifier for recognizing power quality disturbances is implemented and tested under various transient events. The discrete wavelet transform technique is integrated with multiple neural networks using a learning vector quantization network as a powerful classifier. Various transient events are tested, the results show that the classier can detect and classify different power quality
2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2008
Vegetables and fruits are the most important export agricultural products of Thailand. In order t... more Vegetables and fruits are the most important export agricultural products of Thailand. In order to obtain more value-added products, a product quality control is essentially required. Many studies show that quality of agricultural products may be reduced from many causes. One of the most important factors of such quality is plant diseases. Consequently, minimizing plant diseases allows substantially improving quality
ABSTRACT The aim of production line enhancement in any industry is to improve quality and reduce ... more ABSTRACT The aim of production line enhancement in any industry is to improve quality and reduce operating costs by applying various kinds of advanced technology. In order to become more competitive, many sensing, monitoring, and control approaches have been investigated in the textile industry. Automated visual inspection is one area of improvement where real cost savings can be realized over traditional inspection techniques. Manual visual inspection of textile products is expensive and error-prone because of the difficult working environment near the weaving machine. Automated visual detection of fabric defects is particularly challenging due to the large variety of fabric defects and their various degrees of vagueness and ambiguity. This work presents a hybrid application of Gabor filter and two-dimensional principal component analysis (2DPCA) for automatic defect detection of texture fabric images. An optimal filter design method for Gabor Wavelet Network (GWN) is applied to extract texture features from textile fabric images. The optimal network parameters are achieved by using Genetic Algorithm (GA) based on the non-defect fabric images. The resulting GWN can be deployed to segment and identify defect within the fabric image. By using 2DPCA, improvement of defect detection can significantly be obtained. Experimental results indicate that the applied Gabor filters efficiently provide a straight-forward and effective method for defect detection by using a small number of training images but still can generally handle fabric images with complex textile pattern background. By integrating with 2DPCA, desirable results have been simply and competently achieved with 98% of accuracy.
ABSTRACT Image watermarking provides copyright protection and becomes very crucial for ownership ... more ABSTRACT Image watermarking provides copyright protection and becomes very crucial for ownership verification of digital images. In this paper, we investigate the effects of different types of transformations in image watermarking algorithm including discrete cosine transform, discrete wavelet transform, and discrete multiwavelet transform. We also provide a brief overview of the multiwavelet transform since it is relatively new as compared to the other transforms. The efficiencies of these transforms are discussed by evaluating watermarked image quality and robustness of the watermark. Experimental results show that the multiwavelet transform method is superior to other two methods in term of image quality.
In this paper, we propose an image watermarking algorithm using the discrete multiwavelet transfo... more In this paper, we propose an image watermarking algorithm using the discrete multiwavelet transform. The watermark insertion and watermark detection are based on the techniques for the DWT-based image watermarking proposed by Dugad et al. In our method, the watermark is embedded to the multiwavelet transform coefficients larger than some threshold values. We have developed an optimization technique using the
Image watermarking provides copyright protection of digital image by hiding appropriate informati... more Image watermarking provides copyright protection of digital image by hiding appropriate information in the original image in such a way that it does not cause degradation of the perceptual image quality and cannot be removed. The watermarking methods for transform domains are usually achieved by using the discrete cosine transform or the discrete wavelet transform. In this paper, we develop
ABSTRACT Recognition of power quality events by analyzing the voltage and current waveform distur... more ABSTRACT Recognition of power quality events by analyzing the voltage and current waveform disturbances is a very important task for the power system monitoring. This paper presents a new approach for the recognition of power quality disturbances using wavelet transform and neural networks. The proposed method employs the wavelet transform using multiresolution signal decomposition techniques working together with multiple neural networks using a learning vector quantization network as a powerful classifier. Various transient events are tested, such as voltage sag, swell, interruption, notching, impulsive transient, and harmonic distortion show that the classifier can detect and classify different power quality signal types efficiency.
2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2008
Pedestrian detection is one of the most important research contents of road safety. The crucial i... more Pedestrian detection is one of the most important research contents of road safety. The crucial idea behind such pedestrian safety systems is to protect the driver and pedestrian from any accident. In this paper, a pedestrian feature extraction based on color symmetry phases is presented. By examining symmetry phases in multiple color spaces, the segmentation results are significantly improved which
In this paper, we propose digital image watermarking algorithm in the multiwavelet transform doma... more In this paper, we propose digital image watermarking algorithm in the multiwavelet transform domain. The embedding technique is based on the quantization index modulation technique and this technique does not require the original image in the watermark extraction. We have developed an optimization technique using the genetic algorithms to search for optimal quantization steps to improve the quality of watermarked image and robustness of the watermark. In addition, we analyze the performance of the proposed algorithm in terms of peak signal to noise ratio and normalized correlation. The experimental results show that our proposed method can improve the quality of the watermarked image and give more robustness of the watermark as compared to previous works.
Intrinsic images, including reflectance and illumination images, are desirable to many vision app... more Intrinsic images, including reflectance and illumination images, are desirable to many vision applications. An improved method for extracting intrinsic images from a single color image with integrated measures is presented. To start with, the input image convolves with a predefined set of derivative filters. The pixels of filtered images are then classified into reflectance-related or illumination-related using a criterion measure comprising three measures of filtered pixels calculated from the input image. The three measures are denoted as chromatic measure, blur measure, and intensity measure. Finally, the intrinsic images of the input image can be computed from the classification results of the filtered images. Both synthetic and real images have been utilized in our experiments. The results demonstrated that the proposed technique can effectively extract the intrinsic images from a single image.
2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221), 2001
This paper proposes a method to obtain optimal 2 nd -order approximation preserving prefilters fo... more This paper proposes a method to obtain optimal 2 nd -order approximation preserving prefilters for a given orthogonal unbalanced multiwavelet basis. This procedure uses the prefilter construction introduced in [3]. The prefilter optimization scheme exploits the Taylor series expansion of the prefilter combined with the multiwavelet. Using the DGHM multiwavelet with the obtained optimal prefilter, we find that quadratic input signals are annihilated by the high-pass portion of filter bank at the first level of decomposition.
2006 1st International Symposium on Wireless Pervasive Computing, 2006
In this paper, we present an algorithm for robust audio watermarking in wavelet transform domain.... more In this paper, we present an algorithm for robust audio watermarking in wavelet transform domain. Using Daubechies wavelet decomposition, we perform watermark embedding to wavelet coefficients of host audio signal. In enhance security, a pseudo-random permutation is performed to disperse the spatial relationship of the binary watermark image. In our watermark embedding algorithm, we search for the optimal intensity of
Proceedings of 2004 International Symposium on Intelligent Signal Processing and Communication Systems, 2004. ISPACS 2004., 2004
The objective of this paper is to present a new method for automatically detecting, localizing an... more The objective of this paper is to present a new method for automatically detecting, localizing and classifying various types of power quality disturbances. The new method is based on wavelet transform analysis, artificial neural networks, and the mathematical theory of evidence. The proposed detection and localization algorithm is carried out in the wavelet transform domain using multiresolution signal decomposition techniques and the proposed classification method is carried out in the sets of multiple neural networks using a learning vector quantization network. The outcomes of the networks are then integrated using a voting decision making scheme. The performance of the automatic detection and localization have 90.14% accuracy and the error is less than 5%.
TENCON 2005 - 2005 IEEE Region 10 Conference, 2005
This paper proposes a wavelet-based neural network classifier for recognizing power quality distu... more This paper proposes a wavelet-based neural network classifier for recognizing power quality disturbances is implemented and tested under various transient events. The discrete wavelet transform technique is integrated with multiple neural networks using a learning vector quantization network as a powerful classifier. Various transient events are tested, the results show that the classier can detect and classify different power quality
2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2008
Vegetables and fruits are the most important export agricultural products of Thailand. In order t... more Vegetables and fruits are the most important export agricultural products of Thailand. In order to obtain more value-added products, a product quality control is essentially required. Many studies show that quality of agricultural products may be reduced from many causes. One of the most important factors of such quality is plant diseases. Consequently, minimizing plant diseases allows substantially improving quality
ABSTRACT The aim of production line enhancement in any industry is to improve quality and reduce ... more ABSTRACT The aim of production line enhancement in any industry is to improve quality and reduce operating costs by applying various kinds of advanced technology. In order to become more competitive, many sensing, monitoring, and control approaches have been investigated in the textile industry. Automated visual inspection is one area of improvement where real cost savings can be realized over traditional inspection techniques. Manual visual inspection of textile products is expensive and error-prone because of the difficult working environment near the weaving machine. Automated visual detection of fabric defects is particularly challenging due to the large variety of fabric defects and their various degrees of vagueness and ambiguity. This work presents a hybrid application of Gabor filter and two-dimensional principal component analysis (2DPCA) for automatic defect detection of texture fabric images. An optimal filter design method for Gabor Wavelet Network (GWN) is applied to extract texture features from textile fabric images. The optimal network parameters are achieved by using Genetic Algorithm (GA) based on the non-defect fabric images. The resulting GWN can be deployed to segment and identify defect within the fabric image. By using 2DPCA, improvement of defect detection can significantly be obtained. Experimental results indicate that the applied Gabor filters efficiently provide a straight-forward and effective method for defect detection by using a small number of training images but still can generally handle fabric images with complex textile pattern background. By integrating with 2DPCA, desirable results have been simply and competently achieved with 98% of accuracy.
ABSTRACT Image watermarking provides copyright protection and becomes very crucial for ownership ... more ABSTRACT Image watermarking provides copyright protection and becomes very crucial for ownership verification of digital images. In this paper, we investigate the effects of different types of transformations in image watermarking algorithm including discrete cosine transform, discrete wavelet transform, and discrete multiwavelet transform. We also provide a brief overview of the multiwavelet transform since it is relatively new as compared to the other transforms. The efficiencies of these transforms are discussed by evaluating watermarked image quality and robustness of the watermark. Experimental results show that the multiwavelet transform method is superior to other two methods in term of image quality.
In this paper, we propose an image watermarking algorithm using the discrete multiwavelet transfo... more In this paper, we propose an image watermarking algorithm using the discrete multiwavelet transform. The watermark insertion and watermark detection are based on the techniques for the DWT-based image watermarking proposed by Dugad et al. In our method, the watermark is embedded to the multiwavelet transform coefficients larger than some threshold values. We have developed an optimization technique using the
Image watermarking provides copyright protection of digital image by hiding appropriate informati... more Image watermarking provides copyright protection of digital image by hiding appropriate information in the original image in such a way that it does not cause degradation of the perceptual image quality and cannot be removed. The watermarking methods for transform domains are usually achieved by using the discrete cosine transform or the discrete wavelet transform. In this paper, we develop
ABSTRACT Recognition of power quality events by analyzing the voltage and current waveform distur... more ABSTRACT Recognition of power quality events by analyzing the voltage and current waveform disturbances is a very important task for the power system monitoring. This paper presents a new approach for the recognition of power quality disturbances using wavelet transform and neural networks. The proposed method employs the wavelet transform using multiresolution signal decomposition techniques working together with multiple neural networks using a learning vector quantization network as a powerful classifier. Various transient events are tested, such as voltage sag, swell, interruption, notching, impulsive transient, and harmonic distortion show that the classifier can detect and classify different power quality signal types efficiency.
2008 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, 2008
Pedestrian detection is one of the most important research contents of road safety. The crucial i... more Pedestrian detection is one of the most important research contents of road safety. The crucial idea behind such pedestrian safety systems is to protect the driver and pedestrian from any accident. In this paper, a pedestrian feature extraction based on color symmetry phases is presented. By examining symmetry phases in multiple color spaces, the segmentation results are significantly improved which
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