Search Results for "python data analysis" - Page 2

...CT, MRI, PET, etc.) comprises multiple frames which represent slices, phases, timing etc. from the same imaging object. Those images can be saved as multidimensional matrices in Matlab thanks to Matlab's powerful support of multidimensional data representation. However, within Matlab, most of image manipulation functions are limited or tailored for processing two-dimensional matrix. The MatrixUser is a software package which features functions designed and optimized specifically for manipulating multidimensional real or complex data matrix. MatrixUser provides a nice graphical environment for easily performing image analysis tasks including multidimensional image display, matrix (image stack) processing and rendering etc. ...

The OpenCMISS-Zinc Library (opencmiss.org/zinc), or Zinc, is a software library for building interactive graphical modelling and visualisation applications. Models are represented in Zinc as mathematical fields defined over domains, including finite elements with support for high-order basis functions, complex parameter mappings and time variation, and image-based fields. Further fields can be defined by mathematical expressions and algorithms on existing fields, including image...

This MATLAB-based program enables analysis of AFM images. In particular, it allows the user to measure the volume of all distinguishable features in an image and to isolate and sort those particles. As the name implies, LAVA uses Lloyd's Algorithm, also known as k-means sorting, to identify a small set of volumes representative of the actual distribution of particle in the image. Although developed for determining feature volume, LAVA is also completely compatible with other types of...

Malimpa stands for MAtlab Library for IMage Processing and Analysis. It provides functions for 2D/3D grascale/color image creation, filtering, or measurement. It requires, and complements Matlab Image Processing Toolbox. Important notice: the project is now hosted in GitHub, https://github.com/dlegland/matImage

...Face Recognition has always been a popular subject for image processing and this article builds upon the good work by Sergio Andrés Gutiérrez Rojas and his original article (codeproject). The reason that face recognition is so popular is not only it’s real world application but also the common use of principle component analysis (PCA). PCA is an ideal method for recognising statistical patterns in data. The popularity of face recognition is the fact a user can apply a method easily and see if it is working without needing to know to much about how the process is working.

Pink is an image processing library developed at ESIEE Engineering for research and teaching purposes. It contains implementations of over 200 algorithms for image segmentation and filtering.

phpCollect aims to quickly and easily graph, record, and display statistical host data.

VIPS is an image processing suite designed for extremely large images and colorimetry. It consists of a powerful re-usable library and a graphical user interface. http://www.vips.ecs.soton.ac.uk

LeafAnalyser has been developed as a fast throughput leaf shape analysis application. It contains features such as automated image processing, data analysis and interactive 2D/3D graphs.

MIVF - Medical Imaging and Visualization Factory, is a framework for medical applications. It supplies a platform, in which image processing and 3D visualization algorithms can be employed as reusable components (functional modules or plugins).

UIMP(Unified Image Manipulation Program) is an OS independent Image Processing system, which provides over 1000 algorithms and supports web online, console and GUI program.

GeoSciPy is a set of C and Python functions that provide an API for all aspects of Geoscience and Remote Sensing Applications. Functions include reading/writing of many data formats, images, vectors, ..., and processing of images, vectors, ... including map projections, ... The library is written C, using HDF5 as the file format for storage of all remotely-sensed data and ancillary data, as well as processed data.