Search Results for "image analysis algorithm"

itom is an open source software suite for operating measurement systems, laboratory automation and data evaluation. One main application of itom is the development and operation of sensor and measurement system for instance in a laboratory environment. Therefore, the software has to be able to communicate with a wide range of different hardware systems, such as cameras or actuators and should provide a diversified and as complete as possible set of evaluation and data processing methods....

Gem Measure overlays an adjustable polygon onto a gemstone image or video feed and instantly calculates edge length deviations, symmetry, and overall quality. It's designed for jewelers, gemologists, and hobbyists who need quick, accurate measurements without expensive software. Works with USB microscopes, webcams, or any image file. How to Use Open an image (F) or connect a camera (C). Adjust the polygon by dragging its vertices to match the gem outline. Read deviation...

LaueTools is an open-source project for white beam Laue x-ray microdiffraction data analysis including tools in image processing, peaks searching & indexing, crystal structure solving (orientation & strain) and data & grain mapping visualisation. Python 3 Code and new features are now at: https://gitlab.esrf.fr/micha/lauetools

Image analysis software for quantification of cell density in microbial cultures (e.g. S. cerevisiae) growing on solid agar plates. Specialises in detection of extremely low cell densities. Forms part of the Quantitative Fitness Analysis (QFA) workflow: http://research.ncl.ac.uk/qfa/ Suitable for high-throughput, genome-wide analysis of culture libraries when combined with the following qfa R package: http://qfa.r-forge.r-project.org/ This is the version presented, used and demonstrated in the following manuscripts: Lawless et al. 2010 http://dx.doi.org/10.1186/1471-2105-11-287 Addinall et al. 2011 http://dx.doi.org/10.1371/journal.pgen.1001362 Chang et al. 2011 http://dx.doi.org/10.1534/g3.111.000216 Banks et al. 2012 http://dx.doi.org/10.3791/4018 Development has been moved to github, where Colonyzer has undergone several recent improvements, particuarly making installation easier and analysis faster: https://github.com/CnrLwlss/Colonyzer