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A source and channel coding scheme for image transmission over noisy channel is presented in this paper. There is crude block structure in the wavelet coefficient of images. Coding each image blocks independently and reassigning its bitstream can achieve the resynchronization of decoding image in receiving terminal to improve the image's ability to resist noisy. But different image block has different...
Classifying the heterogeneous classes present in the hyper spectral image is one of the recent research issues in the field of remote sensing. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes present in the hyper spectral image are having different textures, textural classification is entertained. Wavelet based...
In this paper a new approach is proposed to recognize gender from the face image. This approach will detect the face from the given image. Radon and Wavelet Transforms are combined to extract key facial features for each face images of male and female. These features will be used to classify the face images of each pattern. We have compared the DCT extracted face feature with our face feature extracted...
Fabric defect detection and classification plays a very important role for the automatic detection in fabrics. This study refers to the four common seen defects of stretch knitted fabrics: laddering, end-out, hole, and oil spot. First of all, wavelet transfer is applied to obtain its wavelet energy to take them as defect features of this image, and then the back-propagation neural network (BPNN) was...
The following topics are dealt with: compressed video indexing; particle swarm optimization; data clustering; image retrieval; video coding; augmented reality; video watermarking; medical image analysis; images fusion; SVM; image segmentation; feature selection; heterogeneous image databases; color texture classification; video surveillance; public transportation; pedestrian detection; Adaboost algorithm;...
The key to surgical planning for breast conservation is tumor localization. An accurate localization of the breast tumor is essential to guide the surgeon to the lesion, and ensure its correct and adequate removal with satisfactory excision margins. Current breast tumor localization techniques are invasive and often result in a cosmetic disfigurement. In this paper, we use the ultrawide band radar-based...
Face recognition has been studied extensively recently. The main difficulty faced by the current face recognition techniques stems from large variations in facial expression, pose and illumination. This paper presents an effective method for face recognition using nonseparable wavelet domain block-based PCA(BPCA) method. Our investigations demonstrate that the constructed nonseparable wavelet can...
It is well-known that most wavelet functions are un-symmetrical and thus fail to satisfy Fourier criterion. These kinds of wavelets cannot be utilized to construct Mercer kernel directly. Based on convolution technique, this paper proposes a novel framework on Mercer kernel construction. The proposed methodology indicates that any of wavelets can generate a wavelet-like kernel basis function, which...
A coarse-classification based tying method for the Contourlet-domain Hidden Markov Tree model (CHMT) solution algorithm is proposed to speed up the parameters estimation; and a general SAR image filtering framework, to which any kind of shift-variant transform can be applied, is generated by applying together with the LOG Transform, mean rectification and cycle-spinning, etc. The proposed coarse classification...
Image classification is an important task in computer vision. In this paper, we propose a supervised method for image classification based on a fast beta wavelet networks (FBWN) model. First, the structure of the wavelet network is detailed. Then, to enhance the performance of wavelet networks, a novel learning algorithm based on the Fast Wavelet Transform (FWTLA) is proposed. It has many advantages...
In this paper we propose a new approach for automated diagnosis and classification of Magnetic Resonance (MR) human brain images, using Wavelets Transform (WT) as input to Genetic Algorithm (GA) and Support Vector Machine (SVM). The proposed method segregates MR brain images into normal and abnormal. Our contribution employs genetic algorithm for feature selection witch requires much lighter computational...
This study chose Quick Bird satellite image with high resolution and spatial information as the resource origin of image classification and used Support Vector Machine (SVM) to achieve the goal on classification. We present two of spatial information which are Principal Component Analysis (PCA) image using 2-D discrete wavelet transform (DWT), and image segmentation. The DWT is used to generate spatial...
In this paper, a three-step classification method is proposed for remote sensing images with the spectral and texture features based on the Support Vector Machine (SVM) classifier. The image is first segmented into regions with the spectral features. Then, texture features are extracted from each region by the undecimated wavelet transform. Third, the SVM is used to classify the image with these extracted...
Optical Characters Recognition (OCR) is one of the active subjects of research since the early days of computer science. There are two main stages in most of OCR systems: features extraction and classification. Artificial Neural Networks and Hidden Markov Models are the most popular classification methods used for OCR systems. In this paper, a method that relays on Fast Wavelets Transform (FWT) for...
In the information society, information security is particularly important. Palmprint recognition for identification provides a new scheme for information security. This paper presents a block statistic method for palmprint identification. Firstly, the method denoised region of interest (ROI) of the palmprint with the first-level wavelet decomposition. Then it blocked the low-frequency sub-image....
Glaucoma is the second leading cause of blindness worldwide. The risk of glaucoma can be determined by calculating the cup to disc ratio in retinal fundus images. To accurately detect the optic cup, kinks or bends in small and medium vessels are important indicators of the cup boundary. In this paper, we present a method of detecting such vessels, through the extraction of patches and generation of...
In order to extract the feature of electroencephalogram (EEG) quickly and efficiently, to improve the classification accuracy rate, band-pass filter and wavelet package were used to get mu and beta rhythms. In the time domain, energy feature was formed by the squared-amplitude of electroencephalogram (EEG) samples over the trials. The subtracted energy value of lead C3 and C4 was averaged by each...
Currently, methods of image tampering detection are divided into two categories, active detection and passive detection. In this paper, we try to review several detecting methods and hope this will offer some help to this field. We will focus on the passive detection method for medical images and show some results of our experiments in which we extract statistical features (IQM and HOWS based) of...
SAR and optical remote sensing image, with highly complementary characteristics, can enhance the integration of information utilization of remote sensing data. Adopting the new Cosmo-Skymed SAR high-resolution image data, we inhibit speckle impact using enhanced Lee filtering. Then we fused this image with a CBERS image using local use standard deviation based on wavelet packet method. Because of...
Based on multifractal analysis in wavelet pyramids of texture images, a new texture descriptor is proposed in this paper that implicitly combines information from both spatial and frequency domains. Beyond the traditional wavelet transform, a multi-oriented wavelet leader pyramid is used in our approach that robustly encodes the multi-scale information of texture edgels. Moreover, the resulting texture...
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