The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Wetland types of Yellow River Delta are various and serious phenomena of 'same object with different spectrum' and 'different object with same spectrum' is one of the reasons caused low classification accuracy. Combination with multi source images is an efficient method to mitigate this influence. In the paper, principal component transform was carried out to Radarsat four polarization data and the...
The present article focuses on the classification of fingerprints. Our aim goal is to unify the process of fingerprint compression, classification and identification. The well known methods suited to these tasks are based on WSQ (Wavelet Scalar Quantization) for compression, Gabor filters for classification and minutiae matching for identification. We propose to use Block Ridgelet Transform (BRT)...
We propose a report on automatic classification of three common types of malignant lymphoma: chronic lymphocytic leukemia, follicular lymphoma, and mantle cell lymphoma. The goal was to find patterns indicative of lymphoma malignancies and allowing classifying these malignancies by type. We used a computer vision approach for quantitative characterization of image content. A unique two-stage approach...
A new rotation invariant texture descriptor based on the difference of offset Gaussian (DooG) and a sub-micro pattern encoding are proposed. We first apply the Gabor wavelet to texture images. We then utilize the DooG to measure the difference between the center positive Gaussian and the neighbor rotated negative one. We encode the local micro texture using our proposed method, a sub-micro pattern...
Image classification often relies on texture characterization. Yet texture characterization has so far rarely been based on a true 2D multifractal analysis. Recently, a 2D wavelet Leader based multifractal formalism has been proposed. It allows to perform an accurate, complete and low computational and memory costs multifractal characterization of textures in images. This contribution describes the...
We propose an texture classification method for the image classification of objects in 2D images. The algorithm is based on recent developments in support vector machines and contourlet transform. The texture classification method is robust in the presence of noise. The method has been implemented and performed experiments on some image data. Our experimental results showed characteristics of our...
In this paper, efforts were made to merge SPOT5 panchromatic image with multispectral images using six different data fusion algorithms, which were Hue-Intensity-Saturation(HIS), Principle Component Analysis(PCA), Kauth-Thomax (K-T) transform, Linear-weighted transform, Brovey fusion and Wavelet transform fusion. We evaluated the fusion images in both subjective and objective factors. The research...
Urban is composed of different critical levels of organization where interactions are stronger within levels than among levels, it is a complex system. Image analysis performed at a unique scale for urban applications is doomed to be incomplete and misleading. This paper presents a multiscale image analysis method based on wavelet transform and watershed transform for urban system. It performs image...
For most coefficients of wavelet image are zero, SPIHT algorithm which divides the list of insignificant pixels(LIS) into type A and type B and carries out classification judgment to each node in the list leads to the time cost increasing to the encoder. This paper introduces a kind of wavelet base(V9/3) with human vision properties and lifting wavelet transform, cancels the classification procedure...
The diffusion weighted imaging (DWI) technique can be utilized to investigate a variety of diseases. We propose an automated system which assists the diagnosis of metabolic brain diseases clinically. In this study, DWI images are preprocessed and exponential apparent diffusion coefficient (eADC) images are produced. The eADC images are later brain extracted and normalized to a standard brain atlas...
In this paper we explain a fully automatic system for airplane detection and tracking based on wavelet transform and Support Vector Machine (SVM). By using 50 airplane images in different situations, models are developed to recognize airplane in the first frame of a video sequence. To train a SVM classifier for classifying pixels belong to objects and background pixels, vectors of features are built...
A new approach for image classification based on the color information, shape and texture is presented. In this work, we use the three RGB bands of a color image in RGB model to extract the describing features. All the images in image database are divided into 6 parts. We use the Daubechies 4 wavelet transform and first order color moments to obtain the necessary information from each part of the...
In this paper we present a novel appearance based approach to the problem of face pose classification. This method suggests the subject-independent pose classification of face images using bilateral filtering and wavelet transform as preprocessing and isometric projection based subspace learning for the extracting of discriminant feature vectors. Our proposed method is evaluated on a large image set...
Gender classification is one of the most challenging problems in the field of pattern recognition. The pixel-based gray image recognition method is quite sensitive to illumination variation and has high dimensions for computation. PCA-based image feature recognition algorithm can reduce the image dimension, but it is only on the basis of optimal entropy to choose face features which neglects the different...
Texture image classification is more and more important. Multi-resolution analysis methods such as wavelet and wavelet packet decompositions are more superior to other classic statistical methods. The wavelet analysis has been intensively used for texture classification with encouraging results. In this paper, two new hybrid methods for invariant pixel regions texture image classification are proposed,...
We investigate a biologically motivated approach to fast visual classification, directly inspired by the recent work [13]. Specifically, trading-off biological accuracy for computational efficiency, we explore using standard wavelet transforms and patch transforms to parallel the tuning of visual cortex V1 and V4 cells, alternated with max operations to achieve scale and translation invariance. A...
This paper proposes a novel method based on Haar wavelet transform and uniform local binary patterns (ULBPs) to recognize ear images. Firstly, ear images are decomposed by Haar wavelet transform. Then ULBPs are combined simultaneously with block-based and multi-resolution methods to describe together the texture features of ear sub-images transformed by Haar wavelet. Finally, the texture features...
Wavelet transform of projection profile of character images has been found to be suitable for machine recognition of handwritten characters. In this work, performance analysis of such a feature using twelve different wavelet filters and different training / test data sets is carried out. A total of twelve thousand eight hundred handwritten isolated Malayalam characters belonging to 33 classes were...
In this paper, we introduce a face recognition approach based on the contourlet transform and support vector machine, which takes technological advantages of both support vector machine and the contourlet transform for feature extraction. The contributions of this paper include the following aspects: (1) support vector machine is successfully applied to face recognition by using the contourlet transform...
In this paper we present an experimental analysis of colour-based texture image classification in order to evaluate whether colour and texture information should be used jointly or separately. Various colour spaces are used for colour information extraction. The complex wavelet transform is used to extract texture information. Results show that colour and texture information should be treated separately...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.