Current methods for thresholding functional magnetic resonance imaging (fMRI) maps are based on the well-known hypothesis-test framework, optimal for addressing novel theoretical claims. However, these methods as typically practiced have a strong bias toward protecting the null hypothesis, and thus may not provide an optimal balance between specificity and sensitivity in forming activation maps...

We present an automatic method for segmentation of white matter, gray matter and cerebrospinal fluid in T1weighted brain MR images. We model images in terms of spatial relationships between near voxels. Brain tissue segmentation is first performed with relative thresholding, a new segmentation mechanism which compares two voxel intensities against a relative threshold. Relative thresholding con...

In this study, a new geocomputing index called the Rain Exposure Index (REI) is proposed. REI can be used for flash flooding prediction due to heavy rainfall accumulation. The index was constructed by computing data from GOES-9 satellite images using combinations of image processing and functional constructs. Water vapour data from GOES-9 satellites were collected from 1 January 20 September, 2...

Wavelet shrinkage denoising methods are widely used for estimation of biological signals from noisy environment. The popular Hard and Soft thresholding filters are commonly used in these methods. In this paper shrinkage method based on a New Thresholding filter for denoising of biological signals is proposed. The efficacy of this filter is evaluated by applying this filter for denoising of ECG ...

This paper presents a selective local thresholding method of a camera based document image for applying character segmentation. It is very difficult to binarize a camera based document image due to inconsistent lighting condition. It makes difficulties of character extraction and recognition. A selective local thresholding method in character region can reduce illumination effect and extract pr...

We propose GLGM (gray-level & gradient-magnitude) histogram as a novel image histogram for thresholding. GLGM histogram explicitly captures the gray level occurrence probability and spatial distribution property simultaneously. Different from previous histograms that also consider the spatial information, GLGM histogram employs the Fibonacci quantized gradient magnitude to characterize spatial ...

Up-down counters are commonly used in the aerospace industry for fault detection thresholding. This paper applies the up-down counter technique to detect wind turbine faults. The thresholding problem involves a tradeoff between false alarms and missed detections. Counter based thresholding can detect smaller faults with higher probability and lower false alarms than is possible using simple con...

The performance of a number of image processing methods depends on the output quality of a thresholding process. Typical thresholding methods are based on partitioning pixels in an image into two clusters. In this paper, a new thresholding method is presented. The main contribution of the proposed approach is the application of the empirical mode decomposition (EMD) on detecting an optimal thre...

Adaptive binarization methodologies threshold the intensity of pixels with respect to adjacent exploiting integral images. In turn, images are generally computed optimally using summed-area-table algorithm (SAT). This document presents a new adaptive technique based on fuzzy through an efficient design modified SAT for integrals. We define this methodology as FLAT (Fuzzy Local Thresholding). Th...

Methods based on thresholding of wavelet coefficients have been found to be popular in the estimation of biological signals from noisy environment. Hard and soft filters are most commonly used in these methods. In this paper a novel thresholding filter for wavelet shrinkage estimation of biological signals is proposed. The proposed novel filter is applied using Visu Shrink rule and top rule to ...