Search Results for "pixel system images"
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Showing 6 open source projects for "pixel system images"
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Qi - Quantitative Imaging (PIV and more)
A collection of MATLAB tools for PIV, PTV, particle sizing, and more.
Qi is a collection of MATLAB tools for the quantitative analysis of flow field images. Our Particle Image Velocimetry (PIV) tool, prana, implements a Robust Phase Correlation kernel for PIV analysis, and now includes Particle Tracking Velocimetry and sizing tools. Tools for pressure calculation, proper orthogonal decomposition (POD), and 3d imaging are under development. -
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Face Recognition System
Face Recognition System Matlab source code
Research on automatic face recognition in images has rapidly developed into several inter-related lines, and this research has both lead to and been driven by a disparate and expanding set of commercial applications. The large number of research activities is evident in the growing number of scientific communications published on subjects related to face processing and recognition. Index Terms: face, recognition, eigenfaces, eigenvalues, eigenvectors, Karhunen-Loeve algorithm. -
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GoIFISH
for the semi-automated analysis of IFISH images
... code is also available for download. To cite this software: "GoIFISH: A system for the quantification of single cell heterogeneity from IFISH images" Trinh A, Rye IH, Almendro V, Helland A, Russness HG, Markowetz F May 2014 -
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flNeuronTool
A Fast Light Neuron Tracing and Editor Tool
The flNeuronTool allows users to reconstruct and proofread neuronal morphologies in light microscopy images. The system incorporates automatic tracing and manual editing of neuron reconstruction into a cooperative 3D interactive visualization-assisted environment, which is a powerful tool for analysis of complex neuronal images. -
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MATLAB GUI and code to map cell distribution around smooth spherical microcarriers beads from laser scanning confocal microscope images
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MADR is a framework for analysis of series of images (2D data) where each pixel position have the same meaning in every image. Based on a statistical analysis, the images can then be visualised together with parameters from the analysis.
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