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A robust semi-supervised method using the mode filter has been presented for learning with partially-labeled training data including label errors. The mode filter has been originally developed for smoothing images contaminated with impulsive noises. However it needs nonlinear optimization which is usually solved with iterative methods. In this paper, we propose a direct solution method with full search...
The challenges associated with wireless vision sensor networks are low energy consumption, less bandwidth and limited processing capabilities. In order to meet these challenges different approaches are proposed. Research in wireless vision sensor networks has been focused on two different assumptions, first is sending all data to the central base station without local processing, second approach is...
Support Vector Machine (SVM) is a useful technique for data classification with successful applications in different fields of bioinformatics, image segmentation, data mining, etc. A key problem of these methods is how to choose an optimal kernel and how to optimize its parameters in the learning process of SVM. The objective of this study is to propose a Genetic Algorithm approach for parameter optimization...
This paper presents a method which based on Fourier-Mellin transform registration algorithm to rotate the archaic epigraph images correction without reference object. In our research range, we improve the traditional methods of edge detection based on the characters of archaic epigraph images, propose the block edge detection method and the multi-scale edge detection method based on Wavelet Transform...
Aiming at threshold uncertainty caused by fuzziness of image for image segmentation, an adaptive thresholding method for gray-level image segmentation using type-II fuzzy sets is proposed . Fuzzy index is got using type-II fuzzy sets technique, that can overcome effectively the uncertainty, histogram peaks value of an image can be find out automatically based on maximum Mahalanobis distance and minimum...
The image segmentation of a robot binocular stereo vision system is the key issue in imaging processing. In this paper, the method of 2-d maximum entropy threshold image segmentation with Chaos PSO algorithm is used to segment the images information collected by a robot vision system, and the algorithm is checked by a real robot binocular stereo vision system. Moreover, compared with previous research,...
With high compression ratio performance, fractal image compression technology becomes a hot topic of research of image compression techniques. However, the encoding time of traditional fractal compression technique is too long to achieve real-time image compression, so it cannot be widely used. Based on the theory of fractal image compression; this paper raised an improved algorithm form the aspect...
The grain size is an important quality index of granular materials. The accurate measurement of it has a guiding significance for technical performances and application of subsequent processing. Currently most of particle detection are done by manual operation such as screening method, which causes many problems as time-consuming measurement and lengthy testing steps. The particle size detection technology...
Abstract-Deficiencies and excess of soybean's plant nitrogen is the key of soybean nutritional diagnosis. Applying image processing technique, this paper studied the leaf images of the six stages of soybean growth, which nitrogen fertilizer applied were 0%, 50%, 100% and 150%. Using image preprocessing, the noise of source image was removed and the areas of interest were enhanced, leaves and background...
Background subtraction is a traditional method for detecting objects in stationary background. However, this traditional method is difficult to detect objects accurately in the real world, because the background is usually cluttered and not completely static. In this paper, we propose an object detection approach using Ant Colony System (ACS) in a MAP-MRF framework. For object segmentation, a MAP-MRF...
Texture segmentation by Pseudo Jacobi -Fourier moments is presented in this paper. Given a window size, moments for each pixel in the image are computed within small local windows, and then texture feature images be obtained by using a nonlinear transducer. Finally, each pixel in the image is classified by K-mean clustering algorithm.
Synthetic aperture radar (SAR) is well adapted to detect ocean pollution independently from daily or weather conditions. Oil slicks have a specific impact on ocean wave spectra because the presence of oil slicks can induce a damping of the backscattering to the sensor and a damping of the energy of wave spectra. Thus oil slicks can be discernible from the radar image. Several algorithms are applied...
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expectation maximization (EM) methodology. The key feature of our approach is related to a top-down hierarchical search for the number of components, together with the integration of the model selection criterion within a modified...
A new segmentation algorithm for the forest fire image based on Fractional Brownian motion and Contour let transform is proposed. Firstly, the algorithm decomposes the image into several sub-bands of multi-scale, location and multi-direction by Contour let transform. Fractional Brownian motion model is performed for low frequency sub-band, and then estimate the Hurst coefficient of each frequency...
Based on isosceles triangle segmentation, a new approach of color image compression has been proposed by using correlation among RGB components and fractal image compression algorithm in this paper. The encoding process in this paper is composed of two steps: transforming color image into gray-level image according to correlation among RGB and compressing fractal image based on isosceles triangle...
The denoising of natural images corrupted by noise is a long established problem in signal or image processing. Noise is signal dependent and is difficult to be removed without impairing image details. Multi-resolution methods are based on image transformations that reduce image resolution and they are able to segment objects of different sizes depending on the chosen resolution. In this work the...
In order to improve the accuracy of multi-moving objects detection in surveillant video, this paper presents a new method of detection and segmentation for moving objects based on SVM (support vector machine). To further enhance the accuracy of segmentation using support vector machine, we modify the kernel function based on its nature, and some experiments have been done to compare with other kernel...
In this paper, a frequency domain feature extraction algorithm for palm-print recognition is proposed, which efficiently exploits the local spatial variations in a palm-print image. The entire image is segmented into several narrow-width spatial bands and a palm-print recognition scheme is developed based on extracting dominant spectral features from each of these bands using two-dimensional discrete...
In order to extract valid information from video, process video data efficiently, and reduce the transfer stress of network, more and more attention is being paid to the video processing technology. The amount of data in video processing is significantly reduced by using video segmentation and key-frame extraction. So, these two technologies have gradually become the focus of research. With the features...
The following topics are dealt with: linear approximation; license plate recognition; color image segmentation; image quantization; wireless video transmission; congestion control; stochastic search; transmembrane helical segments; wavelet transform; semisupervised cluster algorithm; anomaly detection; data privacy; online market information processing; user behavior; particle swarm optimization;...
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