Development of an image processing open-source software for video-surveillance devices

Author(s):  
M. Jerian
2020 ◽  
Vol 26 (S2) ◽  
pp. 2176-2177
Author(s):  
Noah Kraft ◽  
Anette von der Handt

2017 ◽  
Vol 3 (2) ◽  
pp. 199-202
Author(s):  
Markus Reischl ◽  
Andreas Bartschat ◽  
Urban Liebel ◽  
Jochen Gehrig ◽  
Ference Müller ◽  
...  

AbstractHigh-throughput microscopy makes it possible to observe the morphology of zebrafish on large scale to quantify genetic, toxic or drug effects. The image acquisition is done by automated microscopy, images are evaluated automatically by image processing pipelines, tailored specifically to the requirements of the scientific question. The transfer of such algorithms to other projects, however, is complex due to missing guidelines and lack of mathematical or programming knowledge. In this work, we implement an image processing pipeline for automatic fluorescence quantification in user-defined domains of zebrafish embryos and larvae of different age. The pipeline is capable of detecting embryos and larvae in image stacks and quantifying domain activity. To make this protocol available to the community, we developed an open source software package called „ZebrafishMiner“ which guides the user through all steps of the processing pipeline and makes the algorithms available and easy to handle. We implemented all routines in an MATLAB-based graphical user interface (GUI) that gives the user control over all image processing parameters. The software is shipped with a manual of 30 pages and three tutorial datasets, which guide the user through the manual step by step. It can be downloaded at https://sourceforge.net/projects/scixminer/.


2021 ◽  
Vol 3 ◽  
Author(s):  
Robert Haase

Intra- and extra-cellular processes shape tissues together. For understanding how neighborhood relationships between cells play a role in this process, having image processing filters based on these relationships would be beneficial. Those operations are known and their application to microscopy image data typically requires programming skills. User-friendly general purpose tools for pursuing image processing on a level of neighboring cells were yet missing. In this manuscript I demonstrate image processing filters which process grids of cells on tissue level and the analogy to their better known counter parts processing grids of pixels. The tools are available as part of free and open source software in the ImageJ/Fiji and napari ecosystems and their application does not require any programming experience.


2018 ◽  
Vol 7 (1) ◽  
pp. 25-36 ◽  
Author(s):  
Muhammad Dede Yusuf ◽  
RD Kusumanto ◽  
Yurni Oktarina ◽  
Tresna Dewi ◽  
Pola Risma

Robot application in agriculture can ease the farming process, especially as the harvesting robot for seasonal fruit that is available in a short time. The addition of "eye" as the image sensor is an important feature for a harvesting robot. Thanks to the increment of technology, the camera is getting smaller with better performance, and lower prices. The cheap sensors and components make the creation of cheap and effective robot possible. Image processing is necessary for object detection, and open source software is available now for this purpose. This paper proposes BLOB analysis for object detection of 5 fruits with different shapes and colors. The simulation results show that the proposed method is effective for object detection regardless the shapes, colors, and noises.


2014 ◽  
Vol 60 (3) ◽  
pp. 185-190 ◽  
Author(s):  
Michael Henke ◽  
Branislav Sloboda

Abstract This paper presents an easy and effective method to extract tree rings completely from images of tree discs independent of their source. The method uses Active Contours, often used in medical image processing to detect organs, in combination with an optimised image filter based on the Sobel operator to automatically outline the tree rings. Special attention is given to eliminate critical physical irregularities caused by branches, cracks or colourisations. The work resulted in the implementation of a platform independent, free and open source software solution for semiautomatic tree ring segmentation. Comparison to manual measurements shows that the system is dependable and the results are reproducible. The system has been applied to several conifer species.


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