Category：C
-
Time：2019-8-24
Briefly: EigenFace is a face recognition algorithm based on PCA dimensionality reduction. PCA is to maximize the variance of the whole data dimensionality reduction without considering the changes between classes after dimensionality reduction. It regards every pixel of an image as one-dimensional feature, and then trains it with SVM or other machine learning algorithms. But […]
-
Time：2019-8-24
IEEE P802.15 Wireless Personal Area Networks Project IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Title Study Group 4TV Draft 5 Criteria Date Submitted [May 12, 2011] Source Mi-Kyung Oh, Cheolho Shin, Sangsung Choi [ETRI], Soo-Young Chang [CSUS], Chin-Sean Sum [NICT], Betty Zhao [Huawei] E-Mail: [[email protected]] Re: Abstract […]
-
Time：2019-8-23
Analog Serial Communication with Ordinary IO Port Serial Port Communication Protocol The default baud rate of serial port transmission is 96001, the starting bit, the stopping bit and the other 0 bits are 8 bits (note the wrong number on the chart). When transmitting, start from the start bit, start from a low bit of […]
-
Time：2019-8-23
Preface: When we extract the object in the image by threshold segmentation, we need to extract the contour of the object through edge detection. These two methods can basically determine the edge or foreground of the object. Next, what we usually need to do is to fit the foreground of these edges, such as the […]
-
Time：2019-8-22
Contour: A contour represents a series of points (pixels), which constitute an ordered set of points, so a contour can be understood as an ordered set of points. In opencv, a function is provided to return an ordered set of points or an ordered set of points (referring to multiple ordered sets of points). The […]
-
Time：2019-8-21
The example in this paper shares the specific code of the comprehensive example of Opencv perspective transformation for your reference. The specific contents are as follows. Case Background:Correction of the following distorted image The idea of the scheme is as follows:Gray level binary segmentation, closed operation, outline finding, Hough line detection, line sorting, line equation, […]
-
Time：2019-8-20
I. Demand Analysis First is the need: 1. Using affine transform function in OpenCV to realize some basic transformation of image, such as translation, rotation and zooming.2. Learning the principle of perspective transformation, making perspective transformation for a rectangle, and drawing the transformation results. First, the OpenCV function is called to realize perspective transformation, and […]
-
Time：2019-8-19
In this paper, we share the specific code of perspective transformation of OpenCV image geometry transformation for your reference. The details are as follows. 1. Basic Principles The essence of Perspective Transformation is to project an image onto a new view plane. Its general transformation formula is as follows: (u, v) is the original image […]
-
Time：2019-8-18
In this paper, we share the specific code of object extraction and measurement in Opencv3 for your reference. The details are as follows. Case Background:Here is a satellite image of the island’s circumference and area. The idea of the scheme is as follows:Gauss Fuzzy Denoising, Gray Level Binary Extraction of Contours, Closed Operation Filling Gaps […]
-
Time：2019-8-17
The post-80s generation may still have fresh memories of a classic wooden jigsaw puzzle game played in childhood. Generally, it is a 4*4 or 5*5 size hand-held movable board. By moving the position of each small board, the complete image on the board can be obtained. At that time, there was no Internet cafe, and […]
-
Time：2019-8-16
The specific code of OpenCV for mosaic and frosted glass filters is shared for your reference. The details are as follows. I. Mosaic effect The principle of mosaic is to replace all points in a certain range of neighborhood of a pixel in an image with the color of a randomly selected pixel in the […]
-
Time：2019-8-15
Real-time background replacement based on HSV color space: #include<opencv2\opencv.hpp> using namespace cv; Mat replace_and_blend(Mat &frame, Mat&mask); Mat background,frame, hsv, mask,result; int main(int arc, char** argv) { background = imread(“2.jpg”); namedWindow(“input”, CV_WINDOW_AUTOSIZE); imshow(“src”, background); VideoCapture capture; capture.open(“1.mp4”); CvSize size = cvSize(capture.get(CV_CAP_PROP_FRAME_WIDTH), capture.get(CV_CAP_PROP_FRAME_HEIGHT)); VideoWriter writer(“qq.avi”, VideoWriter::fourcc(‘M’, ‘J’, ‘P’, ‘G’),12.0, size, true); while (capture.read(frame)) { imshow(“input”, frame); cvtColor(frame, […]
