Search Results for "patterns"

WingSegment is a MATLAB app-designed tool employing a hybrid approach of computer vision and graph theory for precise insect wing image segmentation. WingSegment detects cells, junctions, Pterostigma, and venation patterns, measuring geometric features and generating Voronoi patterns. The tool utilizes region-growing, thinning, and Dijkstra's algorithms for boundary detection, junction identification, and vein path extraction. It provides histograms and box plots of geometric features, facilitating comprehensive wing analysis. WingSegment's efficiency is validated through comparisons with established tools and manual measurements, demonstrating accurate results. ...

...The archive includes more than 2 million images originally acquired and divided in three different categories: SAMPLING and SAMPLING_PATTERNS (aimed at testing resampling algorithms), COLOR (aimed at testing color rendering on different displays) and PATTERNS (aimed at testing the rendering of standard geometrical patterns). Please cite the following papers when using any image in this archive: * ASUNI N, GIACHETTI A, "TESTIMAGES: A Large Data Archive For Display and Algorithm Testing", Journal of Graphics Tools, Volume 17, Issue 4, 2015, pages 113-125, DOI:10.1080/2165347X.2015.1024298 * ASUNI N, GIACHETTI A, "TESTIMAGES: a large-scale archive for testing visual devices and basic image processing algorithms", STAG - Smart Tools & Apps for Graphics Conference, 2014.

...However, performing the cell counting by tagging the cells in a steady image mosaic increases the reliability of the counts performed. Unfortunately, to build a mosaic of a hemocytometer's grid shows some problem due to the repeated patterns (i.e., the squared blocks of the grid). GridMos is an open-source software tool conceived to build an image mosaic of a hemocytometer's grid. It is optimized to build the mosaic starting from a sequence of overlapping images previously acquired. The Graphical User Interface (GUI) implemented makes GridMos a very user-friendly software tool. ...

...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.