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ilastik [1] is a user-friendly free open source software for image classification and segmentation. No previous experience in image processing is required to run the software. Since 2018 ilastik is further developed and maintained by Anna Kreshuk's group at European Molecular Biology Laboratory.
Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]
OpenCV (Open Source Computer Vision Library) is a library of programming functions mainly for real-time computer vision. [2] Originally developed by Intel, it was later supported by Willow Garage, then Itseez (which was later acquired by Intel [3]).
Built on top of OpenCV, a widely used computer vision library, Albumentations provides high-performance implementations of various image processing functions. It also offers a rich set of image transformation functions and a simple API for combining them, allowing users to create custom augmentation pipelines tailored to their specific needs. [3]
In computer vision and image processing, Otsu's method, named after Nobuyuki Otsu (大津展之, Ōtsu Nobuyuki), is used to perform automatic image thresholding. [1] In the simplest form, the algorithm returns a single intensity threshold that separate pixels into two classes, foreground and background.
CVIPtools A complete open-source GUI-based Computer Vision and Image Processing software, with C functions libraries COM based dll along with two utilities program for algorithm development and batch processing. Fiji (software), an image processing package based on ImageJ; KNIME - an open-source data mining environment supporting image analysis ...
It uses Intel's OpenCV library for fast image processing and contains interfaces for USB, FireWire and GigE cameras, as well as AVI files. [ 2 ] Since version 4, SwisTrack's pipeline is built by the user from components which interact with each other and pass data through data channels.
The pruning algorithm is a technique used in digital image processing based on mathematical morphology. [1] It is used as a complement to the skeleton and thinning algorithms to remove unwanted parasitic components (spurs). In this case 'parasitic' components refer to branches of a line which are not key to the overall shape of the line and ...