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.
A novel image fusion algorithm using adaptive Unit-Linking Pulse Coupled Neural Networks (ULPCNN) is put forward. Firstly, ULPCNN threshold function is improved, and then the null interconnection and the adaptive interconnection ULPCNN are formed. Secondly, the nonlinear mapped ULPCNN time matrix can be obtained, which can represent the characteristic of the single pixel, but can reflect the pixel...
In Wire Electric Discharge Machining (WEDM) the wire electrode wears out with wear of the workpiece, this worsens the surface quality because of deposition of three-fourth area of solidified material on the eroded surface of wire. Higher material removal rate, lowers the electrical conductivity of the dielectric and results in reduction of gap between wire electrode and workpiece. The paper reports...
The researches on images fusion have attracted more attention due to the increasing demands. A number of pixel-based and region-based image fusion algorithms are described in certain criterions. In this work, a novel region-based image fusion method is proposed, which explores pulse couples neural network (PCNN) to produce a region map. Characteristics of each region are calculated and the region-based...
The period of Arnold transformation is a key parameter, which affects its application effectiveness in the fields of image encryption, digital watermark, information hiding, etc. However, the previous research results on the period of discrete two-dimensional Arnold transformation are very rough estimation and lack of practical application value. By analyzing the relationship between the image order...
A technique for intelligent processing is proposed for the analysis of brain magnetic resonance images. This paper presents segmentation and detection technique of tumor, edema and healthy tissues from fluid attenuated inversion recovery magnetic resonance images of brain with the help of composite feature vectors comprising of empirically developed functions of higher order wavelets and statistical...
Interval type-2 fuzzy logic can be applied to perform image processing and pattern recognition. In this work a new type-2 fuzzy logic method is applied for edge detection in images and the results are compared with three different traditional techniques for the same goal with the type-2 edge detection outperforming the other techniques.
Artificial neural network (ANN) is an important part of artificial intelligence, it has been widely used in remote sensing classification research field. Wetlands remote sensing classification based on ANN is difficult, because of the complex feature of wetlands areas. The purity of training samples for remote sensing image supervised classification is difficult to guarantee that will affect the classification...
We propose a three-state series neural network for effective propagation of context and uncertainty information for image parsing. The activation functions used in the proposed model have three states instead of the normal two states. This makes the neural network more flexible than the two-state neural network, and allows for uncertainty to be propagated through the stages. In other words, decisions...
We propose to use energy minimization in MRFs for matching-based image recognition tasks. To this end, the Tree-Reweighted Message Passing algorithm is modified by geometric constraints and efficiently used by exploiting the guaranteed monotonicity of the lower bound within a nearest-neighbor based classification framework. The constraints allow for a speedup linear to the dimensionality of the reference...
Clustered micro calcifications (MCs) are one of the early signs of breast cancer. In this paper, we propose a new computer aided diagnosis (CAD) system for automatic detection of MCs in two steps. First, pixels corresponding to potential micro calcifications are found using a multilayer feed-forward neural network. The input of this network consists of 4 wavelet and 2 gray-level features. The output...
Document Script Identification (DSI) is a very useful application in document processing. This paper presents a method for this application that uses a new noise tolerant feature, the Downgraded Pixel Density feature. Compared to other features widely used in existing DSI solutions, this new feature is much more robust to variations in slant, font and style of printed documents. Experimental results...
This paper presents scratch restoration method that can deal with scratches of various lengths and widths in old film. The proposed method consists of detection and reconstruction. The detection is performed using texture and shape properties of the scratches: first, each pixel is classified as scratches and non-scratches using a neural network (NN)-based texture classifier, and then some false alarms...
Answering to a query like when a particular document was printed is quite helpful in practice especially forensic purposes. This study attempts to develop a general framework that makes use of image processing and pattern recognition principles for ink age determination in printed documents. The approach, at first, computationally extracts a set of suitable color features and then analyzes them to...
We address here the problem of color constancy and propose a new method to achieve color constancy based on the statistics of images with color cast. Images with color cast have standard deviation of one color channel significantly different from that of other color channels. This observation is also applicable to local patches of images and ratio of the maximum and minimum standard deviation of color...
The clustering method “Fuzzy-C-Means” (FCM) is widely used in image segmentation. However, the major drawback of this method is its sensitivity to the noise. In this paper, we propose a variant of this method which aims at resolving this problem. Our approach is based on an adaptive distance which is calculated according to the spatial position of the pixel in the image. The obtained results have...
When the conventional method of parameter estimation is used to construct the RPC model, the uncertain factors can result in inconsistency between the RPC model and the reality. The inconsistency shows up as evident systematic error in the constructed RPC model. To tackle the problem, a non-parametric component is introduced on the base of the parametric model to account for the unknown factors and...
In this paper, we propose a three-layer spatial sparse coding (TSSC) for image classification, aiming at three objectives: naturally recognizing image categories without learning phase, naturally involving spatial configurations of images, and naturally counteracting the intra-class variances. The method begins by representing the test images in a spatial pyramid as the to-be-recovered signals, and...
Reducing the dimension of local descriptors in images is useful to perform pixels comparison faster. We show here that, for computing the NL-means denoising filter, image patches can be favourably replaced by a vector of spatial derivatives (local jet), to calculate the similarity between pixels. First, we present the basic, limited range implementation, and compare it with the original NL-means....
This paper presents a method based on RBF neural networks to predict the specific region cloud cover, which has the feature of time serial and nonlinear. Using this method, we can train the RBF neural networks and find out the nonlinear relations among historical cloud cover data, to predict future time of cloud cover. Experiment results show that the method provided a kind of viable intelligent way...
This paper introduces a new mammogram enhancement algorithm using the human visual system (HVS) based image decomposition. A new enhancement measure based on the second derivative is also introduced to measure and assess the enhancement performance. Experimental results show that the presented algorithm can improve the visual quality of fine details in mammograms. The HVS-based image decomposition...
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.