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开源软件名称(OpenSource Name):carolinepacheco/lbp-library开源软件地址(OpenSource Url):https://github.com/carolinepacheco/lbp-library开源编程语言(OpenSource Language):C++ 96.8%开源软件介绍(OpenSource Introduction):LBP LibraryLast Page Update: 26/09/2018 Latest Library Version: 1.0.1 (see Release Notes for more info). The LBP Library is a collection of eleven Local Binary Patterns (LBP) algorithms developed for background subtraction problem. The algorithms were implemented in C++ based on OpenCV. A CMake file is provided and the library is complatible with Windows, Linux and Mac OS X. The library was tested successfully with OpenCV 2.4.x and OpenCV 3.4.x. List of the algorithms available in the LBP Library
CitationIf you use this library for your publications, please cite it as:
List of collaboratorsAndrews Sobral and Cristina Lazar. Example code#include <iostream>
#include <opencv2/opencv.hpp>
#include "lbplibrary.hpp"
using namespace lbplibrary;
int main(int argc, char **argv)
{
cv::VideoCapture cap(0);
if (!cap.isOpened())
return;
LBP *lbp;
lbp = new OLBP;
//lbp = new ELBP;
//lbp = new VARLBP;
//lbp = new CSLBP;
//lbp = new CSLDP;
//lbp = new XCSLBP;
//lbp = new SILTP;
//lbp = new CSSILTP;
//lbp = new SCSLBP;
//lbp = new BGLBP;
cv::Mat frame, img_lbp;
while (1)
{
cap >> frame;
cv::resize(frame, frame, cv::Size(320, 240));
imshow("capture", frame);
show_multi_histogram(frame);
cv::cvtColor(frame, frame, CV_BGR2GRAY);
//cv::GaussianBlur(frame, frame, cv::Size(7, 7), 5, 3, cv::BORDER_CONSTANT);
imshow("gray", frame);
show_histogram("gray_hist", frame);
lbp->run(frame, img_lbp);
cv::normalize(img_lbp, img_lbp, 0, 255, cv::NORM_MINMAX, CV_8UC1);
cv::imshow("lbp", img_lbp);
show_histogram("lbp_hist", img_lbp);
if (cv::waitKey(10) >= 0)
break;
}
delete lbp;
} Release Notes:
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2023-10-27
2022-08-15
2022-08-17
2022-09-23
2022-08-13
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