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Library for processing and manipulating images.
:warning: This repository is no longer actively maintained. It previously dealt with Non-Intrusive Load Monitoring (NILM), focusing on predicting household appliance status from aggregated power load data. We explored different thresholding methods and evaluated deep learning models for regression and classification tasks.
A set of algorithms and other cool things that I learned while doing image processing with openCV using C++ and python.
Paddy Leaf Disease Detection Using SVM Classifier - Matlab Code
Use of Image Processing to detect brain tumour in MRI Scan
A collection of code for processing images
Image processing code for blob detection and feature extraction in MATLAB. Paper Reference: Detecting jute plant disease using image processing and machine learning. Find the full text here: http://ieeexplore.ieee.org/document/7873147/
Inverse Filtering, Wiener Filter, Image Restoration, Hough Transform, Image segmentation using watershed, thresholding, region growing and region splitting and merging
Medical Image Processing Techniques
opencv for face detection, segmentation, recognition, lane findings,
Two methods for segmenting skin on ultrasound B-mode images
A project on Image Processing, leveraging PyQt5 for a user-friendly GUI and implementing essential operations like Low Pass Filter, Downsampling, Upsampling, Thresholding, and Negative Image Generation. It offers a visually engaging experience while exploring the realm of image processing techniques.
Interactive image viewer and processing application for computer vision research and real-time parameter tuning with OpenCV
See movement patterns over time using Python and OpenCV
This GitHub repository serves as a valuable resource for researchers, developers, and enthusiasts working with AUVs, providing a range of image processing algorithms and tools tailored to enhance visual perception and analysis in underwater scenarios.
A work-in-progress web application for ProADV. This project aims to revive the ProADV website, providing a user-friendly interface for the Python package that processes and analyzes acoustic Doppler velocimeter (ADV) data.
Water level detection using draft marker readings, through the means of computer vision, machine learning and optical flow methods
A Morphological Hessian Based Approach for Retinal Blood Vessels Segmentation and Denoising Using Region-Based Otsu Thresholding
The work presented explains how to segment the brain tumour area in absence of interaction with user basing his technique on a saliency map constructed from three different resonance techniques.
Implementation of various image processing methods from scratch in python.
Shadow Detector
A gesture based Mouse controller using openCV and PyMouse
An image processing library, including methods of filtering, object detection, noise reduction, etc
This application can be used to quickly view how different Thresholding Methods work on images. Selected threshold method can be applied for bulk images in a folder, results are saved in a user selected folder with histograms.
OCT-A ANALYSIS is an ImageJ macro that automates operations to analyze OCT-A angiograms. It is especially useful for case series studies. ➔Accelerate data collection ➔Improve the reproducibility of results
Image Classification, Object Detection, Image Segmentation, Instance Segmentation and Pose Estimation
Simple image filtering and segmentation on MCU and FPGA
Easy to use edge detection library using canny edge detection algorithm and sobel operators, with some other utilities to remove boiler-plate code for applications.
Drum Rhythm Pattern Generator
Basic Image Processing in C, Matlab and Python
Two-Stage Multithreshold Otsu method.
Complete resource for people wanting to learn Computer Vision with the latest OpenCV4, Dlib and DeepLearning
This project is a comprehensive image processing application designed to perform a wide range of operations on digital images. It provides a user-friendly interface for opening, manipulating, and analyzing images using various techniques and algorithms. It is built using C# and WPF, leveraging the MVVM (Model-View-ViewModel) design pattern.