We demonstrate an enterprise Dynamic Thresholding System for data-agnostic management of monitoring flows. The dynamic thresholding based on data historical behavior enables adaptive and more accurate control of business environments compared to static thresholding. We manifest the main blocks of a complex analytical engine that is implemented in VMware vCenter Operations Manager as a principal...

We propose a soft thresholding approach to the minimum description length wavelet denoising. Our method is based on combining two-part coding with normalized maximum likelihood universal models to give a soft thresholding denoising criterion. Experiments with the proposed MDL soft thresholding method indicate that our denoising criterion leads to fairly similar performance as with the well-know...

This paper proposes a local adaptive thresholding method based on a water #ow model, in which an image surface is considered as a three-dimensional (3-D) terrain. To extract characters from backgrounds, we pour water onto the terrain surface.Water #ows down to the lower regions of the terrain and "lls valleys. Then, the thresholding process is applied to the amount of "lled water for character ...

Variance-based thresholding method is a very effective technology for image segmentation. However, its performance is limited in traditional one-dimensional and twodimensional scheme. In this paper, a novel two-dimensional variance thresholding scheme to improve image segmentation performance is proposed. The two-dimensional histogram of the original and local average image is projected to one-...

The drawback of the conventional multilevel thresholding methods is high computational cost since they do exhaustive search among exponentialy growing number of possible thresholds to optimize the objective functions. In this paper a new multilevel thresholding method based on cuckoo search (CS) algorithm is proposed in order to overcome this obstacle. The optimal thresholds are found by maximi...

Vehicular traffic in urban areas faces congestion challenges that negatively impact our lives. The infrastructure associated with intelligent transportation systems provides means for addressing the areas. This study proposes an effective and scalable vehicular avoidance methodology. It introduces a thresholding mechanism to predict avoid during route computation. Our methodology was evaluated ...

Image thresholding is a very common image processing operation, since all image processing schemes need some sort of operation of the pixels into different classes. In order to determine thresholds, most methods analyze the histogram of the image. The optimal thresholds are often found by either minimizing or maximizing an objective function with respect to the values of the thresholds. In this...

-Maximum likelihood thresholding methods are presented on the basis of population mixture models. It turns out that the standard thresholding proposed by Otsu, which is based on a discriminant criterion and also minimizes the mean square errors between the original image and the resultant binary image, is equivalent to the maximization of the likelihood of the conditional distribution in the po...