Computer Vision and Image Recognition algorithms for R users
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Updated
Jul 3, 2024 - C++
Computer Vision and Image Recognition algorithms for R users
Image Processing: Segmentation Using Otsu Threshold Method
A collection of image processing algorithms written in pure Go.
Otsu's method thresholding and image binarization on GPU in CUDA
parallel image processing algorithms using pymp
Convex Polygon Detection
A Canny edge detection function implemented by us from scratch that can use either double thresholding, recursion, or the otsu's thresholding method for an adaptive threshold. Algorithm used for Otsu's method and the recursive approach can be seen in the papers included in this repository.
Repository referent to the Basic Education Program (2014)
A playing card detection plugin for ImageJ.
Simple image filtering and segmentation on MCU and FPGA
An Editor to perform rotation,conversion of the color model,Histogram equalization,Histogram chart,Mean filtering,and converting to the binary color of an image.
Satellite library(fft, variogram,...)
Two-Stage Multithreshold Otsu method.
Basic numpy implementation of Otsu and Niblack algoritms
OTSU method is a global adaptive binarization threshold image segmentation algorithm.
Through the use of Contrast Limited Adaptive Histogram Equalization (CLAHE) filters, completed with otsu filters, a direct reading of car license plates with success rates above 70% and an acceptable time is achieved
Implementation of a Shape Detection pipeline for recognizing those famous traffic bollards found in Amsterdam without any Image Processing libraries
From some files of images and labels obtained by applying the project presented at https://github.com/ashok426/Vehicle-number-plate-recognition-YOLOv5, the images of license plates are filtered through a threshold that allows a better recognition of the license plate numbers by pytesseract. On 05/23/2022, a new version is introduced. On 07/04/20…
Counting cells in a blood smear using convolution as the pattern matching strategy
In water index calculation, gets the best threshold and full area of water according to known parts or approximation of water.
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