opencv-093-对象检测(LBP特征介绍)

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知识点

局部二值模式(Local Binary Pattern)主要用来实现2D图像纹理分析。其基本思想是用每个像素跟它周围的像素相比较得到局部图像结构，假设中心像素值大于相邻像素值则则相邻像素点赋值为1，否则赋值为0，最终对每个像素点都会得到一个二进制八位的表示，比如11100111。假设3x3的窗口大小，这样对每个像素点来说组合得到的像素值的空间为[0~2^8]。这种结果称为图像的局部二值模式或者简写为了LBP。

代码（c++,python）

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#include <opencv2/opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;
CascadeClassifier faceDetector;
String haar_data_file = "D:/opencv-4.0.0/opencv/build/etc/lbpcascades/lbpcascade_frontalface_improved.xml";
int main(int artc, char** argv) {
	Mat frame, gray;
	vector<Rect> faces;
	VideoCapture capture(0);
	faceDetector.load(haar_data_file);
	namedWindow("frame", WINDOW_AUTOSIZE);
	while (true) {
		capture.read(frame);
		cvtColor(frame, gray, COLOR_BGR2GRAY);
		equalizeHist(gray, gray);
		faceDetector.detectMultiScale(gray, faces, 1.2, 1, 0, Size(30, 30), Size(400, 400));
		for (size_t t = 0; t < faces.size(); t++) {
			rectangle(frame, faces[t], Scalar(0, 0, 255), 2, 8, 0);
		}
		char c = waitKey(10);
		if (c == 27) {
			break;
		}
		imshow("frame", frame);
	}

	waitKey(0);
	return 0;
}
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"""
对象检测(LBP特征介绍)
"""

import cv2 as cv

capture = cv.VideoCapture(0)
detector = cv.CascadeClassifier("D:/software/opencv4/build/etc/lbpcascades/lbpcascade_frontalface_improved.xml")

while True:
    ret, image = capture.read()
    if not ret:
        break

    faces = detector.detectMultiScale(image, scaleFactor=1.05,
                                      minNeighbors=1, minSize=(30, 30), maxSize=(300, 300))
    for x, y, width, height in faces:
        cv.rectangle(image, (x, y), (x + width, y + height), (0, 0, 255),
                     2, cv.LINE_8, 0)
    cv.imshow("faces", image)

    c = cv.waitKey(50)
    if c == 27:
        break

cv.destroyAllWindows()

结果

代码地址

github