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Surface-Reconstruction-from-Point-Clouds
Surface Reconstruction from Point Clouds by Point Cloud Library (PCL) and CGAL-Color-multi-focus-image-fusion-using-Guided-and-Bilateral-filter-based-on-focus-region-detection-in
This code impliments a multi-focus color image fusion method based on focus region detection with edge preseve using bilateral filter and guided filter in discrete wavelet transform (2DWT). Firstly, a novel focus region detection method is estimated, which uses guided filter to refine the rough focus maps obtained by bilateral filter and difference operator. Then, An initial decision map is got via the pixel-wise maximum rule, and optimized to generate final decision map by using guided filter again. Finally, the fused image is obtained by the pixel-wise weighted-averaging rule with the final decision map via inverse transform.Guided-Bilateral-Filter-based-Medical-Image-Fusion-Using-Visual-Saliency-Map-in-the-Wavelet-Domain
Guided-Bilateral Filter-based Medical Image Fusion Using Visual Saliency Map in the Wavelet DomainBinary-Image-classification
Binary Image classification using ImageDataGenerator in KerasPolyp-Detection-and-Segmentation-from-Capsule-Endoscopy
To analyze the large scale CE data exams automatic image processing, computer vision, and learning algorithms. An automatic polyp detection algorithms have been implineted with deep learning approach. The polyp detection in colonoscopy in CE is a challenging problem still now.Real-time-implementation-of-Harris-Corner-Detector-HCD-on-a
A CUDA C++ based real-time implementation of Harris Corner Detector (HCD) algoritm simulation for color imageCFD-Simulation-in-Porous-Medium
This code is capable of simulating of flows through materials with complex, porous structure. In this way, the whole process of importing files containing the porous geometry, generating the computational mesh and running CFD simulation can be performed in MATLAB2D-Heat-Equation-Using-Finite-Difference-Method-with-CUDA
This code is designed to solve the heat equation in a 2D plate with CUDA-Opengl. After solution, graphical simulation appears to show that how the heat diffuses throughout the medium within time interval selected in the code. Solving the 2 Dimensional Heat conduction equation in the generalized form, we used FEM technique.Integration-of-cloud-and-cgal-c-
Integration of PCL and CGAL libraryUnderwater-Image-Contrast-Enhancement-using-Type-2-Fuzzy-Set
A java implimentation of underwater image contrast enhancement using type-2 fuzzy setParalell-computing-of-Hausdorff-distance-measure-for-a-vector-wit-a-given-reference-point
The Hausdorff distance is a mathematical construct to measure the "closeness" of two sets of points or a single set to a refence point that are subsets of a metric space. Here we impliment the distance using CUDA. This program will return the Hausdorff distance between a set of points with a single given data points. The code that computes the Hausdorff distance for a very large vector using parallel approach.SIFT-based-visual-tracking
This code impliments a robust and faster visual tracking framework using shift-invariant features (SIF) and the optical flow in belief- propa- gation (BF) algorithm for efficient processing in real scenarios. SIFT with BF algorithm build invariant features to correspond the regions of interest across frames.Display-video-using-OpenGL
To display very high resolution video directly with OpenGL and OpenCV on Qt5Parallle-implimentation-of-Numerical-solution-for-hyperbolic-partial-differential-equations-based-on
The Lax-Wendroff scheme used the finite differences schemes and is derived in a parallel numerical technique. Here the approach used originally by Lax and Wendroff is given, using a model of hyperbolic partial differential equation.Deep-learning-practice-codes-
Several deep learning applications have design using Python on GPU on LinuxSURF-features-extraction-from-an-image-sequenc
SURF features extraction from an image sequence on pythonParallel-image-sharpening-on-CIDA
Image sharpen using NPP with CUDAStatistical-Image-Segmentation-on-GPU
Statistical Image Segmentation on GPUVariational-Autoencoder-for-image-denoising
Variational Autoencoder for image denoising algorithm implimented by PythorchCamera-calibration
Automatic Camera calibration using OpenCV an ViPSLow-illumination-medical-image-contrast-sharpening
Underexposed medical image contrast sharpeningsurface_reconstruct_ply_demo
surface reconstruction from unstructured 3d point cloud data using cgal and pclparallel-implimentation-of-Laplacian-Edge-Detectors-for-color-large-images-using-CUDA.-
We create a 5x5 kernel and use to Laplacian Edge Detectors kernel with second order derivatives. The laplacian edge detector is extremely sensitive to noise. To reduce noise we use the Gaussian blur.Polygonal-triangular-meshe-using-ospray-c-
This repository contains the code by using ospray C++ library for the generation of triangular meshe on arbitrary set of points.Low-light-image-enhance-using-Java
Images captured in outdoor scenes can be highly degraded due to poor lighting conditions. These images can have low dynamic ranges with high noise levels that affect the overall performance of computer vision algorithms. To make computer vision algorithms robust in low-light conditions, use low-light image enhancement to improve the visibility of an image. To enhance low-light images, we using fuzzy image processing techniques in Java.Convex-hull-reconstruction-and-partitioning-from-RGBD-scanned-data
Convex hull reconstruction and partitioning from 3D RGBD scanned cloud data by pcl and cgalGastrointestinal-Endoscopy-Anomaly-Segmentation-on-Colonoscopy-Images-Using-U-Net
A deep learning method, ingraft-U-Net, is proposed to segment polyps using Melanoma Skin frames. Ingraft-U-Net is a modified version of UNet, which comprises three stages, including the preprocessing, encoder, and decoder stages.Von-Karman-vortex-street-modeling-by-the-Navier-Stokes-equations
In computational fluid dynamics, a Von Karman vortex street is a repeating pattern of swirling vortices caused by the unsteady separation of flow of a fluid around blunt bodies. It is named after the engineer and fluid dynamicist Theodore von Karman. For the simulation, we propose to simulate the Navier-Stokes equation into a rectangular domain with a circular hole of a given diameterCode-for-parallel-Recursive-Newton-s-Algorithm-using-MPI
we have just coded to implement parallel Newton’s recursive algorithm. To accomplish this, we first partition the problem and fitted each partition into master-slave by MPI mode. First, we need to have: (a) The number of interpolation points. (b) A grid of points at which the interpolation is to be exact. (c) An array containing the function we wish to interpolate evaluated at the interpolating grid. (d) An array to store the Newton differencing coefficientsMelanoma-Skin-Anomaly-Segmentation-on-Colonoscopy-Images-Using-U-Net
A deep learning method, ingraft-U-Net, is proposed to segment polyps using Melanoma Skin frames. Ingraft-U-Net is a modified version of UNet, which comprises three stages, including the preprocessing, encoder, and decoder stages.opencv-android-gradle
opencv and androidMedical-image-colorization-using-deep-GANs
Deep GANs color correction method uses to reconstruct a clean color image by deep convolutional neural networks (CNNs) traing on gray images with ground truth.Practice-Python
There are several algorithms are implemented by Python on Linux.contour-detection-for-color-image
contour detection for color image using Visp c++ libraryJava-Computer-Vision-Codes
Java Codes for different Computer Vision algorithmsOpenCV-and-ViSP-with-C-
Integration of OpenCV and ViSP to solve dynamic features trackingdeep_convolutional_autoencoder_image_denoising_model
deep convolutional autoencoder for image denoisingGood-Features-to-Track-
Good Features to Track from real-time videoConvex_Hull-from-Cloud-Points
Convex hull construction from Cloud Points using pcl and cgalPython-basic
python basic for convolutional neural networksLow-level-image-features-detection
A parallel algorithm for low level image features detection using CUDALocal-features-matching-using-OpenCV-C-
Local features matching using OpenCV with C++Transferring-styles-in-Deep-Covnets
Deep learning method for transferring stylesMelanoma-segmentation-using-deep-learning
This code proposes a novel deep learning-based, fully automated approach to skin lesion segmentation, including sophisticated pre and postprocessing approaches. We use three deep learning models, including UNet, deep residual U-Net (ResUNet), and improved ResUNet (ResUNet++).Color-Correction-and-Preserving-on-GPU
Run a CUDA kernel that writes image data to a GL buffer or texture image. A live display via CUDA Graphics Interop mode on Ubuntu and CUDA-11.0 Driver.AKAZE-local-features-matching
AKAZE local features matchingSemantic-Segmentation-deep-learning
Semantic segmentation describes the process of associating each pixel of an image with a class label, (such as flower, person, road, sky, ocean, or car).Low-light-Image-Enhancement-Using-Deep-Convolutional-Network
A Convolutional Neural Networks (CNNs) is directly learns an end-to-end mapping between low light and bright images. The low-light image enhancement in this code solved as a machine learning problem using tensorflow library. This model considred different metrics SSIM, PSNR and entropy as loss function for improve contrast lowand hazy images.Endoscopy-image-denoising-using-patch-correction-with-deep-convolutional-neural-networks-DCNNs-
Deep Image Patch (DIP) correction method uses to reconstruct a clean image by deep convolutional neural networks (DCNNs) traing on noisy images with different noise model and ground truth.Cancer-cells-counting-in-a-co-cultured-image
This algorithm performs automated detection, measurement, and levelling of co-cultured cells. Each cell is identified and characterized by probabilistic hesitant fuzzy set with several local descriptors (entropy, fuzzy index, fuzzy connectivity,etc. ), which are used to define an optimal threshold to segment individual cells.Visual-Enhancement-of-X-ray-Tomography
Visual Enhancement of X-ray Tomography Aid to Interpretation of Pneumonia Malformation via Intuitionistic Fuzzy Special Sets and Fuzzy SimilarityPolyp-Anomaly-Segmentation-on-Colonoscopy-Images-Using-U-Net
A deep learning method, ingraft-U-Net, is proposed to segment polyps using colonoscopy frames. Ingraft-U-Net is a modified version of UNet, which comprises three stages, including the preprocessing, encoder, and decoder stages.Love Open Source and this site? Check out how you can help us