- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2018 International Conference On Advances in Communication and Computing Technology (ICACCT) - Sangamner, India (2018.2.8-2018.2.9)] 2018 International Conference On Advances in Communication and Computing Technology (ICACCT) - An Analysis of Wavelet Based Dual Digital Image Watermarking Using SVD
摘要： Intellectual properties are being obtained and reproduced easily. This raises a serious question on the ownership of images. Hence content owners and service providers seek protection of digital multimedia through watermarking. Though watermark is inserted in host image it becomes difficult to prove ownership due to various attacks affecting the image. Hence watermarking should be as robust as possible maintaining the fidelity. As wavelet based image watermarking resembles the human visual system, it is gaining vital importance in protecting copyright information. In this paper a hybrid scheme based on DWT and SVD is implemented. Two watermarks are inserted in host image one by one. After decomposing the primary watermark image into four bands, SVD is applied to each band, and the same secondary watermark is embedded by modifying the singular values. In this way new watermark is generated which is then embedded into host image. Analysis of the method is done after performing different attacks such as rotation, addition of Gaussian and Poisson noise, average filtering etc. on the watermarked host image. The paper also implements dual image watermarking schemes based on DWT and SVD separately. Correlation coefficient of extracted secondary watermark is 0.23481 in SVD based technique whereas in DWT based technique it is 0.74443 for Gaussian noise attack. On the other hand for DWT-SVD based method it is 0.88701. Thus performance of combined DWT-SVD dual image watermarking is proven optimised in comparison with the previously mentioned two methods.
关键词： singular value decomposition,optimisation technique,correlation coefficient,robustness,discrete wavelet transform,Watermark
更新于2025-09-10 09:29:36
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[IEEE 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom) - Ostrava, Czech Republic (2018.9.17-2018.9.20)] 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom) - Automated Gait Analysis using a Kinect Camera and Wavelets
摘要： Studies of Parkinson’s Disease (PD) have generated particular interest in factors such as gait and posture patterns and fall risk. Human gait patterns involve a basic gait cycle that is composed of two phases: stance and swing. With gait analysis, we can derive values for spatiotemporal variables such as the walking speed, cadence, and stride length from these stance and swing phases. In this paper, we use a low-cost, quick-setup, and portable system to capture gait signals, and propose a novel method for automatically obtaining gait phases (swing and stance) using wavelets and a Kinect camera. We tested this method on six PD patients and six healthy subjects in a clinical context, finding that it could classify the gait phases with 93% accuracy, compared with clinical judgment. Such a procedure could allow clinicians to rapidly, easily, and non-invasively diagnose and assess PD patients via objective and automatic data analysis.
关键词： gait analysis,Kinect,Parkinson’s disease,gait,wavelet,swing,spatiotemporal,stance
更新于2025-09-10 09:29:36
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[IEEE 2018 2nd International Conference on Engineering Innovation (ICEI) - Bangkok (2018.7.5-2018.7.6)] 2018 2nd International Conference on Engineering Innovation (ICEI) - Diabetic retinopathy fundus image classification using discrete wavelet transform
摘要： Diabetes is an incurable disease which erodes away body slowly, this disease in becoming common and becoming a cause of social distress. The only solution to this problem is early detection of disease and take precautionary measure to keep its effects to minimum. Since it affects various parts of body, the affected organ also includes eye which is very sensitive to any kind of distress. Diabetic Retinopathy effects of diabetes on eye retina, which includes rupturing of retina blood vessels and abnormal growth of blood vessels in retina, which ultimately causes blindness. Diabetic Retinopathy can be identified by examining the retinoscopy images. In this paper, retinoscopy images were processed using wavelet transform. Wavelet coefficients extracted from the images were obtained to identify Diabetic Retinopathy. KNN and SVM were used to classify the retinoscopy images. This papers have shown remarkable improvement as compared to previous studies, with KNN at 98.16 % accuracy and SVM at 97.85 % accuracy.
关键词： sensitivity,specificity,Discrete Wavelet Transform (DWT),accuracy,KNN,Diabetic Retinopathy (DR),histogram equalization,SVM
更新于2025-09-10 09:29:36
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[IEEE 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) - Coimbatore (2018.4.20-2018.4.21)] 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT) - Denoising of Iris Image Using Stationary Wavelet Transform
摘要： In Therapeutic images, the analysis activities, for example, object recognition and feature extraction will assume the key part. These errands will end up troublesome if the pictures are defiled with noises. Currently the development of complex algorithms became a new research area. Creating is a troublesome errand since fine points of interest in a medical picture implanting analytic data ought not be devastated evacuation. A commotion considerable lot of the wavelet based denoising calculations utilize DWT (Discrete Wavelet Transform) in the deterioration stage which is experiencing shift variance and lack of directionality. To overthrow this in this paper we are proposing the denoising strategy which utilizes Undecimated Wavelet Transform to break down the picture and we played out the shrinkage task to wipe out the noise from the picture. In the shrinkage step we utilized semi - soft and stein thresholding functions alongside customary hard and soft thresholding functions and confirmed the reasonableness of various wavelet families for the denoising of therapeutic pictures. The outcomes demonstrated that the denoised picture utilizing SWT (Stationary Wavelet Transform) have a superior harmony amongst smoothness and exactness than the DWT. To survey the nature of denoised pictures, the different measurements we utilized are MSE (Mean Squared Error), SSIM (Structural similarity index measure), UQI (Universal Quality Index), PSNR (Peak signal-to-noise ratio), AD (Average Difference), ST(Structural Content), MD (Maximum Difference). NAD (Normalized Absolute Error).
关键词： Stationary Wavelet Transform,Wavelet Shrinkage,Discrete Wavelet Transform
更新于2025-09-09 09:28:46
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Discrete Wavelet Transform (DWT) Assisted Partial Least Square (PLS) Analysis of Excitation-Emission Matrix Fluorescence (EEMF) Spectroscopic Data Sets: Improving the Quantification Accuracy of EEMF Technique
摘要： In the present work, it is shown that quantitative estimation efficiency of the partial least square (PLS) calibration model can be significantly improved by pre-processing the EEMF with discrete wavelet transform (DWT) analysis. The application of DWT essentially reduces the volume of data sets retaining all the analytically relevant information that subsequently helps in establishing a better correlation between the spectral and concentration data matrices. The utility of the proposed approach is successfully validated by analyzing the dilute aqueous mixtures of four fluorophores having significant spectral overlap with each other. The analytical procedure developed in the present study could be useful for analyzing the environmental, agricultural, and biological samples containing the fluorescent molecules at low concentration levels.
关键词： Partial least square analysis,Discrete wavelet analysis,Fluorophores,Wavelet analysis,Excitation-emission matrix fluorescence
更新于2025-09-09 09:28:46
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Shearlet-Based Feature Extraction for the Detection and Classification of Age-Related Macular Degeneration in Spectral Domain Optical Coherence Tomography Images
摘要： Age-related macular degeneration (AMD) is an eye disease that usually affects central vision in people older than 50 years owing to accumulation of fluid in the macular region of the retina. Optical coherence tomography (OCT) is an imaging modality that is being widely used nowadays for the detection of abnormalities in the eye. In this work, a shearlet transformYbased method is proposed for automated detection of AMD. The 2-dimensional horizontal slices of spectral domain OCT imaging data are used as input images. Images are first converted to gray scale and denoised using bilateral filter. Denoised images are decomposed by applying shearlet transform and 10 textural features are extracted from the cooccurrence matrices of high-frequency transform coefficients. Based on these features, the OCT images are classified as normal or AMD using support vector machine and k-nearest neighbor classifiers. Results obtained using shearlet-based features are compared with that of wavelet transformYbased features. Best results are obtained when shearlet-based features are classified using support vector machine.
关键词： Shearlet transform,Wavelet transform,Support vector machine,Optical coherence tomography,K-nearest neighbor,Age-related macular degeneration
更新于2025-09-09 09:28:46
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Image compensation using wavelet transform for tilt servo control in holographic data storage system
摘要： A holographic data storage system is very important in the division of a mass storage device. In this regard, tilt servo control is the main problem in the study of holographic data storage system. Tracking servo and tilt servo control are very important research area in holographic data storage system. In this paper, we propose two algorithms. The ?rst algorithm is image compensation using the wavelet transform method and the second algorithm is intelligent servo control using fuzzy rules for the exact tilt control in the holographic data storage system. We need to obtain a good pattern in binary data using a CMOS camera. We have developed two step-by-step operations. Firstly, to obtain exact image data, image data compensation carried out by the wavelet transform method. Finally, we have realized an intelligence control model using fuzzy rules, which was generated by a subtractive clustering algorithm. Therefore, we control radial and tangential tilt servo control using fuzzy rules in a holographic data storage system and perform image data compensation by the wavelet transform method. Our system does not require responses in the tilt servo control system. Therefore, this system has the advantage terms of time. Consequently, the practical pattern of tilt servo control was found by an intelligence algorithm through image processing in the holographic data storage system.
关键词： wavelet transform,tilt servo control,image processing,holographic data storage system,fuzzy rules
更新于2025-09-09 09:28:46
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[IEEE 2018 IEEE International Conference on Mechatronics and Automation (ICMA) - Changchun (2018.8.5-2018.8.8)] 2018 IEEE International Conference on Mechatronics and Automation (ICMA) - Full Quaternion based Color Image Fusion
摘要： In this paper, the local variance based full quaternions are used to describe image structure. The new structure is different from the real quaternion based method. Image fusion is performed by quaternion transform. The classical framework is applied to fusion images. The color wavelet information is expressed by quaternion wavelet. In order to measure the performance of several wavelet-based image fusion methods, an image fusion assessment method is used in this paper. Two types of source image are used to perform the experiments, four-level wavelet decomposition based assessment method is used to assess the images. Low frequency coefficient of wavelet decomposition matrix is used to fuse images by pixel average value method. Then the performance the methods are evaluated by some experiments. The results show that the information entropy of maximum pixel value and average grads is the greatest. The proposed method gives the best performance in the experiments.
关键词： Image fusion,Information Entropy,Full quaternion,Wavelet transform
更新于2025-09-09 09:28:46
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[IEEE 2018 24th International Conference on Pattern Recognition (ICPR) - Beijing, China (2018.8.20-2018.8.24)] 2018 24th International Conference on Pattern Recognition (ICPR) - Human Gait Recognition with Micro-Doppler Radar and Deep Autoencoder
摘要： The micro-Doppler signals from moving objects contain useful information about their motions. This paper introduces a novel approach for human gait recognition based on backscattered signals from a micro-Doppler radar. Three different signal techniques are utilized for the extraction of micro-Doppler features via time-frequency and time-scale representations. To classify the human motions into various types, this paper presents a deep autoencoder with the use of local patches extracted along the spectrogram and scalogram. The network configuration and the learning parameters of the deep autoencoder, which are considered as hyperparameters, are optimized by a Bayesian optimization algorithm. Experimental results produced by the proposed technique on real radar data show a significant improvement compared to several existing approaches.
关键词： Short-time Fourier Transform,micro-Doppler radar,deep autoencoder,S-method,wavelet transform,Bayesian optimization
更新于2025-09-09 09:28:46
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Secure Image Watermarking Based on LWT and SVD
摘要： Nowadays, digital watermarking is employed for authentication and copyright protection. In this paper, a secure image watermarking scheme based on lifting wavelet transform (LWT) and singular value decomposition (SVD), is proposed. Both LWT and SVD are used as mathematical tools for embedding watermark in the host image. In this work, the watermark is a speech signal which is segmented into shorted portions having the same length. This length is equal to 256 and these different portions constitute the different columns of a speech image. The latter is then embedded into a grayscale or color image (the host image). This procedure is performed in order to insert into an image a confidential data which is in our case a speech signal. But instead of embedding this speech signal directly into the image, we transform it into a matrix and treated it as an image ("a speech image"). Of course, this speech signal transformation permits us to use LWT-2D and SVD to both the host image and the watermark ("a speech image"). The proposed technique is applied to a number of grayscale and color images. The obtained results from peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) computations show the performance of the proposed technique. Experimental evaluation also shows that the proposed scheme is able to withstand a number of attacks such as JPEG compression, mean and median attacks. In our evaluation of the proposed technique, we used another technique of secure image watermarking based on DWT-2D and SVD.
关键词： Speech image,color image,lifting wavelet transform,grayscale image,singular values decomposition,secure,watermark,image watermarking
更新于2025-09-09 09:28:46