A local Gaussian filter and adaptive morphology as tools for completing partially discontinuous curves

This paper presents a method for extraction and analysis of curve--type structures which consist of disconnected components. Such structures are found in electron--microscopy (EM) images of metal nanograins, which are widely used in the field of nanosensor technology. The topography of metal nanograins in compound nanomaterials is crucial to nanosensor characteristics. The method of completing such templates consists of three steps. In the first step, a local Gaussian filter is used with different weights for each neighborhood. In the second step, an adaptive morphology operation is applied to detect the endpoints of curve segments and connect them. In the last step, pruning is employed to extract a curve which optimally fits the template

A pilot study on discriminative power of features of superficial venous pattern in the hand

The goal of the project is to develop an automatic way to identify, represent the superficial vasculature of the back hand and investigate its discriminative power as biometric feature. A prototype of a system that extracts the superficial venous pattern of infrared images of back hands will be described. Enhancement algorithms are used to solve the lack of contrast of the infrared images. To trace the veins, a vessel tracking technique is applied, obtaining binary masks of the superficial venous tree. Successively, a method to estimate the blood vessels calibre, length, the location and angles of vessel junctions, will be presented. The discriminative power of these features will be studied, independently and simultaneously, considering two features vector. Pattern matching of two vasculature maps will be performed, to investigate the uniqueness of the vessel network / L’obiettivo del progetto è di sviluppare un metodo automatico per identificare e rappresentare la rete vascolare superficiale presente nel dorso della mano ed investigare sul suo potere discriminativo come caratteristica biometrica. Un prototipo di sistema che estrae l’albero superficiale delle vene da immagini infrarosse del dorso della mano sarà descritto. Algoritmi per il miglioramento del contrasto delle immagini infrarosse saranno applicati. Per tracciare le vene, una tecnica di tracking verrà utilizzata per ottenere una maschera binaria della rete vascolare. Successivamente, un metodo per stimare il calibro e la lunghezza dei vasi sanguigni, la posizione e gli angoli delle giunzioni sarà trattato. Il potere discriminativo delle precedenti caratteristiche verrà studiato ed una tecnica di pattern matching di due modelli vascolari sarà presentata per verificare l’unicità di quest

Modeling and tracking relative movement of object parts

Video surveillance systems play an important role in many civilian and military applications, for the purposes of security and surveillance. Object detection is an important component in a video surveillance system, used to identify possible objects of interest and to generate data for tracking and analysis purposes. Not much exploration has been done to track the moving parts of the object which is being tracked. Some of the promising techniques like Kalman Filter, Mean-shift algorithm, Matching Eigen Space, Discrete Wavelet Transform, Curvelet Transform, Distance Metric Learning have shown good performance for keeping track of moving object. Most of this work is focused on studying and analyzing various object tracking techniques which are available. Most of the techniques which are available for object tracking have heavy computation requirements. The intention of this research is to design a technique, which is not computationally intensive and to be able to track relative movements of object parts in real time. The research applies a technique called foreground detection (also known as background subtraction) for tracking the object as it is not computationally intensive. For tracking the relative movement of object parts, a skeletonization technique is used. During implementation, it is found that using skeletonization technique, it is harder to extract the objects parts

Visualizing the inner structure of N-body data

N-body simulations produce a large amount of data that must be visualized in order to extract interesting features. This data consists of thousands of particles, each with a number of properties such as velocity, mass, and acceleration, that are persisted across hundreds of time steps. Rendering these points using traditional means quickly leads to a image that is satu- rated because the number of particles is greater than the number of pixels available. Volume rendering, and particularly splatting, seeks to remedy this and allows one to see inside the volume and discern the inner structure. The definition of inner structure itself can vary and is usually determined using one of the observable properties of the particles

Автоматические измерения в металлографии

Quantitative analysis of the structure of metals and alloys is an important part of modern metal science. To obtain quantitative data and build dependencies, metallographic image processing programs are used, oriented both for scientific research and for use in industry. Programs capable of automatically performing metallographic analysis are of great interest to consumers. When advertising such programs, it is often claimed that they allow quantitative analysis of the structure with virtually no time. The purpose of this work was to determine the time spent on quantitative metallographic analysis in some image processing programs presented on the Belarusian market. Connected and unconnected metallographic objects were considered. It is shown that automatic quantitative analysis is possible for unconnected objects (powders, cast iron graphite). The time required is within a minute. For connected objects (structures of metals and alloys after metallographic etching), the time required to detect objects and obtain digital data is 10–40 min or more, depending on the complexity of the object, which is unacceptable for factory laboratories that analyze a large number of samples per shift. Therefore, it is recommended that potential users of metallographic image processing software always require a substantive demonstration of the automatic measurement capabilities of the proposed software.Количественный анализ структуры металлов и сплавов является важной частью современного металловедения. Для получения количественных данных и построения зависимостей используются металлографические программы обработки изображений, ориентированные как на научные исследования, так и для использования в промышленности. Большой интерес у потребителя вызывают программы, способные автоматически проводить металлографический анализ. При рекламе таких программ зачастую утверждается, что они позволяют провести количественный анализ структуры практически без затрат времени. Целью данной работы являлось определение затрат времени на количественный металлографический анализ в некоторых программах обработки изображений, представленных на белорусском рынке. Рассматривались связанные и несвязанные металлографические объекты. Показано, что для несвязанных объектов (порошки, графит чугуна) возможен автоматический количественный анализ; затраты времени при этом составляют в пределах минуты. Для связанных объектов (структуры металлов и сплавов после металлографического травления) затраты времени на обнаружение объектов и получение цифровых данных составляют 10–40 мин и более в зависимости от сложности объекта, что неприемлемо для заводских лабораторий, которые анализируют большое количество образцов за смену. Поэтому потенциальным потребителям программ обработки металлографических изображений рекомендуется всегда требовать предметной демонстрации возможности автоматических измерений предлагаемого программного обеспечения

Keeping track of worm trackers

C. elegans is used extensively as a model system in the neurosciences due to its well defined nervous system. However, the seeming simplicity of this nervous system in anatomical structure and neuronal connectivity, at least compared to higher animals, underlies a rich diversity of behaviors. The usefulness of the worm in genome-wide mutagenesis or RNAi screens, where thousands of strains are assessed for phenotype, emphasizes the need for computational methods for automated parameterization of generated behaviors. In addition, behaviors can be modulated upon external cues like temperature, O2 and CO2 concentrations, mechanosensory and chemosensory inputs. Different machine vision tools have been developed to aid researchers in their efforts to inventory and characterize defined behavioral “outputs”. Here we aim at providing an overview of different worm-tracking packages or video analysis tools designed to quantify different aspects of locomotion such as the occurrence of directional changes (turns, omega bends), curvature of the sinusoidal shape (amplitude, body bend angles) and velocity (speed, backward or forward movement)

Spatial Reconstruction of Biological Trees from Point Cloud

Trees are complex systems in nature whose topology and geometry ar