Three-dimensional (2D) cell culture models have emerged as the basis for improved cell systems biology. However, there is a gap in robust computational techniques for segmentation of these model systems that are imaged through confocal or deconvolution microscopy. The main issues are the volume of data, overlapping subcellular compartments and variation in scale or size of subcompartments of in...

For Autonomous Ground Vehicles, modelling of the terrain is important for predicting future behaviours and control options. Current terrain modelling is able to identify geometric hazards but has a limited ability to identify complex terrain characteristics. This paper presents a method for segmenting and classifying terrain types based on range data to establish a geometric model of the terrai...

In this paper, a copyright protection method for digital image with 1/T rate forward error correction (FEC) is proposed. In the proposed method, the original image is lossless and the watermark is robust to malicious attacks including geometric attacks such as scaling, rotation, cropping, print-photocopy-scan, and scaling-cropping attacks and nongeometric attacks such as low-pass filtering, sha...

To proposing a voting model for groups with members of unequal power and proficiency, we present some models for rank ordering efficient candidates, by extending the ideas of some authors. Then, we propose a new methodology to rank the ranking models for the performance indices of only DEA efficient candidates based on a classical voting model. Also, an approach for combining the results obtain...

In this work we propose a novel geometric clustering algorithm based on the Tensor Voting Framework (TVF). More precisely, we propose the construction of a weighted graph by means of the information diffused by TVF during the vote casting step. This graph, which summarizes informations related to the manifold geometric structure, was used for clustering purposes. To this aim, we applied the wel...

Since the existing floating car map-matching algorithms lead to high error rate when GPS data sampling rate is low, we propose a global-voting map matching algorithm. Based on floating car GPS track data, the algorithm do not only consider the influence to matching process caused by the topological information of road network but also the different spatial distance of GPS track data. In this ma...

We develop a model for predicting the probability of incorrect, random matches when using a geometric hashing based recognition scheme. To estimate the vote for random matches we approximate the voting function by a discrete function and use the binomial distribution. The resulting probability distribution of votes for random matches is compared with experiments that have a set of artificially ...

This paper presents a Devnagari Numerical recognition method based on statistical discriminant functions. 17 geometric features based on pixel connectivity, lines, line directions, holes, image area, perimeter, eccentricity, solidity, orientation etc. are used for representing the numerals. Five discriminant functions viz. Linear, Quadratic, Diaglinear, Diagquadratic and Mahalanobis distance ar...

This paper presents a generalization of the random dot product model for networks whose edge weights are drawn from a parametrized probability distribution. We focus on the case of integer weight edges and show that many previously studied models can be recovered as special cases of this generalization. Our model also determines a dimension–reducing embedding process that gives geometric interp...