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.
Natural disasters such as earthquakes and tsunamis often have a devastating effect on human life and cause noticeable damage to infrastructure. Active research has been ongoing to mitigate the impact of these catastrophes and preclude the economic losses. The existing methods that utilize pre-event and post-event images not only require the immediate and guaranteed availability of the appropriate...
In the web pages contains large and vast amount of data, which is rich source of information available to everyone in the world through Internet. However the web page is combination of noisy data like navigational link, advertisements, menus, footer, etc and informative data, so the complexity may increases for main content extraction from web pages. To access main content hand crafted rule technique...
In this paper two methods for blind source separation of nonstationary signals, such as electroencephalogram output, applied to time frequency distributions are compared through implementation in a virtual instrument. Both methods are based on image processing approaches, but adopt different strategies for solving the blind source separation problem: the first method is based on a data clustering...
Building damage information is an important basis of earthquake disaster loss assessment, it is also one of judgement index of earthquake intensity. In the process of using remote sensing image for earthquake disaster information acquisition and earthquake emergency rescue, building damage information extraction technique is the key to get accurate disaster information. In this paper, based on the...
Urine analysis reveals the presence of many problems and diseases in human body. Manual microscopic urine analysis is time consuming, subjective to human observation, and causes mistakes. Computer aided automatic microscopic analysis can overcome these problems. This paper introduces a comprehensive approach for automating procedures for detecting and recognition of epithelial cells in microscopic...
Feature Selection (FS) has become one of the most active research topics in the area of data mining. It performs to remove redundant and noisy features from high-dimensional data sets. A good feature selection has several advantages for a learning algorithm such as reducing computational cost, increasing its classification accuracy and improving result comprehensibility. In the supervised FS methods...
The research of a determining system of flow image was made, which aimed at tracer particle image obtained by experiment, using digital image processing and analysis, pattern recognition and artificial intelligence. Qualitative and quantitative analysis was used on flow field of torque converter with this system. According to the characteristic of experiment, identifying and tracking the trail of...
Data reduction is an important step in knowledge discovery from data. The high dimensionality of databases can be reduced using suitable techniques, depending on the requirements of the data mining processes. In this work, Rough set theory (RST) has been used as such a tool with much success. RST enables the discovery of data dependencies and the reduction of the number of attributes contained in...
Mobile context modeling is a process of recognizing and reasoning about contexts and situations in a mobile environment, which is critical for the success of context-aware mobile services. While there are prior work on mobile context modeling, the use of unsupervised learning techniques for mobile context modeling is still under-explored. Indeed, unsupervised techniques have the ability to learn personalized...
There are many different types of surface defects on semiconductor integrated chips (IC's) caused by various factors during manufacturing process, such as scratch, flash, resin bleed, melting and void. These defects must be detected and classified by an inspection system for productivity improvement and effective process control. Among these defects, in particular, resin bleed and melting are the...
In order to determine the optimal thresholds in image segmentation, an effective image threshold segmentation method is presented that base on Fuzzy logic. A new fuzzy entropy is defined, that is not only related to the membership (fuzzy domain) but also related to the probability distribution (space domain), it can respond to the variety of image input information. In addition, by introducing a novel...
In this paper, an effective multi-threshold image segmentation method is proposed based on the measure of an adaptive fuzzy maximum entropy. In the traditional image segmentation algorithms with fuzzy entropy, C-threshold is usually determined by 2*C parameters at least, which are generally searched by a conventional genetic algorithm (GA) or simulated anneal algorithm (SA). Adaptive fuzzy entropy...
A technique utilizing an entropy measure is developed for automatically tuning the segmentation of screening mammograms by minimum spanning trees (MST). The lack of such technique has been a major obstacle in previous work to segment mammograms for registration and applying mass detection algorithms. The proposed method is tested on two sets of mammograms: a set of 55 mammograms chosen from a publicly...
The segmentation method based on the optimization of only one criterion does not work well for a lot of images; even when equipped with the optimal value of the threshold of its single criterion, the segmentation program does not produce a satisfactory result. In this paper, image segmentation based on multiobjective optimization is presented. It combines 2-D maximum entropy and 2-D Otsu method using...
For the purpose of color image segmentation, an unsupervised peak value searching algorithm was proposed, which was used to determine the approximate dominant color components of image. First, the local peaks of 3D color histogram within the neighborhood of 3 times 3 times 3 were located. The corresponding color values of local peaks were regarded as initial clustering centers, and the number of local...
To resolve the problem of large angle and large scale image registration, an improved approach combining log-polar and SIFT is proposed. Firstly, the log-polar technique is implemented in order to achieve the preliminary registration result as well as estimate the arbitrary rotations parameters and large scale changes. Secondly, image is segmented into sub-blocks and six candidates of sub-blocks are...
Image processing bears some fuzziness in nature, as a effective mathematical tool for handling the ambiguity, Fuzzy set theory is introduced in the paper to define a new kind of fuzzy entropy, namely two-dimension fuzzy Tsallis entropy (TFTE) and applied in image segmentation following the maximum entropy principle. To overcome the huge calculational burden when generalizing one-dimension entropy...
In this work an ignorance-based fuzzy clustering algorithm is presented. The algorithm is based on the entropy-based clustering algorithm proposed by Yao et al.. In our proposal, we calculate the total ignorance instead of using the entropy at each data point to select the data point as the first cluster center. The experimental results show that the ignorance-based clustering improves the data classification...
A key frame extraction algorithm based on sub-shot segmentation and entropy computing is proposed. Firstly the reconstructed matrix of each frame in shots is computed through sub-space projection. Secondly sub-shot segmentation is processed according to the difference of singular value between frame and its reconstructed matrix, as well as difference of histogram feature between frame and mean value...
The presence of microcalcifications clusters, which appear as small bright spots in mammographic images, can be considered as a very important sign for breast cancer diagnosis. They can, however, be hard to detect due to their size and low contrast from surrounding normal tissue. In this paper, a new fuzzy-based method is presented to provide an appropriate segmentation of microcalcifications. This...
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.