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.
This paper present results of on-line control loop performance assessment using non-Gaussian statistical and fractal measures. Research shows importance of loop quality indexes that are not biased with Gaussian assumption about signal characteristics. Industrial data show frequent fat-tail properties and thus relevant indexes are proposed, like non-Gaussian statistical factors or persistence fractal...
We propose a simple yet efficient steganalytic algorithm for watermarks embedded by two state-of-the-art 3D watermarking algorithms by Cho et al. The main observation is that while in a clean model the means/variances of Cho et al.’s normalized histogram bins are expected to follow a Gaussian distribution, in a marked model their distribution will be bimodal. The proposed algorithm estimates the number...
This paper proposes and evaluates an algorithm to automatically detect the cataracts from color images. Currently, methods available for cataract detection are based on the use of either fundus camera or DSLR camera; both are very expensive. The main motive behind this work is to develop an inexpensive, robust and convenient algorithm which in conjugation with suitable devices will be able to diagnose...
Detecting forgeries in images especially those involved in Copy-Move forgery could become a challenging prospect in the acreage of image forensics. The significance of detecting such forgeries comes to light, given the rise of such malpractices. Now we will see a approach using ASIFT which is planned to expose regions which have been copied and then pasted in another region to either duplicate information...
In this paper we introduce a generalization of the similarity based TOPSIS by using the Bonferroni mean. By generalizing similarity computation between an alternative and the ideal solution we also create an effect, where the ranking of alternatives can change depending on parameter value selection. For this purpose we apply the histogram ranking method to take into consideration the variability of...
In the new Steganographic technique, hiding is based on the difference between the secret message value and the pixel value of the green component of the image. The proposed method works in the spatial domain of the image. We check the difference value between secret byte ASCII (American Standard Code for Information Interchange) value and the pixel ASCII value. For comparison embedding is initially...
In this paper we describe a novel digital image watermarking method using local binary patterns (LBP). Local binary patterns are known for their robust texture describing capabilities and digital watermarking used in proving the ownership of a multimedia content. In this work we propose a LBP synthesis or inverse LBP matching process and its applicability to digital image watermarking. LBP synthesis...
We consider linear programs where some parameters in the objective functions are unknown but data are available. For a risk-averse modeler, the solutions of these linear programs should be picked in a way that can perform well for a range of likely scenarios inferred from the data. The conventional approach uses robust optimization. Taking the optimality gap as our loss criterion, we argue that this...
In this document an algorithm is proposed to identify the state (available/occupied) of the parking spaces in outdoor areas. The algorithm was developed based on two features: the average local entropy, and the standard deviation of the average entropies of subregions of each parking space. The algorithm delivers a binary map, which contains the number of each parking space with its attributes such...
In this paper, a new unsupervised approach is proposed for the segmentation of Multiple Sclerosis (MS) lesions in multimodality Magnetic Resonance (MR) images. The proposed segmentation scheme is based on joint histogram modelling followed by false positive reduction and alpha matting, which is used to deal with the tissue density overlap problem and partial volume effects in MR images. Firstly, the...
This paper presents two new methods for robust parameter estimation of mixtures in the context of MR data segmentation. The head is constituted of different types of tissue that can be modeled by a finite mixture of multivariate Gaussian distributions. Our goal is to estimate accurately the statistics of desired tissues in presence of other ones of lesser interest. These latter can be considered as...
Decision based non-linear filtering is widely used for the removal of impulsive noise. Various robust statistical estimators of scale are in use for determining the threshold of the filtering process. Real-time filtering requires this estimation to be computationally efficient and realizable within the system constraints. This paper proposes the use of Interquartile range (IQR) for filtering impulsive...
This paper presents a novel multi-features fusion tracking algorithm based on local kernels learning. Histograms of multiple features are extracted based on sub image patches within the target region, and the features fusion weights are calculated respectively for each patch according to the discriminability of features. It means that the same feature employed in different sub image patches gets different...
Local Binary Patterns (LBP) and its variants are widely used for texture classification. In this paper we propose a new variant of LBP descriptor called the extended Gaussian filtered Local Binary Patterns (GF-LBP) which is robust to illumination changes, noise and captures more informative edge-like features for classification. Experiments on a colonoscopy image dataset with 2100 images for binary...
A novel distinctive descriptor named MSOGH is proposed, which is able to well represent the interest region and is robust to photometric transformations and geometric transformations. According to intensity order, subregions are firstly constructed. Then feature descriptor of the subregion is computed by point permutation of the sample points in each subregion. Finally, feature descriptor of the region...
This paper is based on real application whose task was to recognize characters printed on metal ingots. The problem is that the surface of ingots is very uneven — ingots are either hot, or cut by rough instrument, the printing machine can be worn down, etc. Therefore, the first difficulty was to separate characters from the background and the second one was the fact that the separated characters are...
In this paper, a robust homography estimation method is proposed to match multiview images in the uncalibrated case. This method formulates a new loss function to verify homography hypothesis, which combines models of key-point consensus and appearance similarity. In the consensus model, Lap lace distribution is exploited to better characterize the imprecision of key points. And in the appearance...
A task of blind evaluation of additive Gaussian noise variance in images is considered. One stage of many methods used for this purpose is obtaining local estimates of noise variance in blocks (scanning windows) of small size tessellating an image. For this purpose, we propose to use robust estimators of sample scale. Several such estimators are studied for cases of pure additive noise and mixed additive...
An automatic text recognizer needs, in first place, to localize the text in the image the more accurately possible. For this purpose, we present in this paper a robust method for text detection. It is composed of three main stages: a segmentation stage to find character candidates, a connected component analysis based on fast-to-compute but robust features to accept characters and discard non-text...
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.