OSI represents Open System Interconnection. It was produced by the International Organization for Standardization (ISO) located in Geneva, Switzerland, and the consultative committee for international Telephone and Telegraph (CCITT).OSI was created to develop a frequent standard of network structure throughout the globe. It supports a general idea of inter-process communication so ... Read More

The presentation layer changes the data from an application layer into the device native internal mathematical structure and encodes communicated information into a displayable output format.It executes the code changes, document compressions, security encryption, etc. It also defines the data as per the software/hardware environment of the hub. For instance, ... Read More

The session layer supports establishing, controlling, and eliminating a session or dialogue between the two end frameworks. It generates the session, handles the packets sent back and forth during the session and removes the session. The dialogue type/session type is also defined through half-duplex or full-duplex.The session layer also supports ... Read More

Physical layer is the shortest layer in the model. This layer is feasible for initiating, preserving, and deactivating a physical circuit between two end frameworks.The Physical Layer is vital for transmitting bits from one device to another device. It can change the series of bits into electric signals, light signals, ... Read More

OSI represents Open System Interconnection. The OSI reference model is a seven-layered architecture and is created in a hugely structured method. Each layer in the model has specific sets of procedures, functions, and protocols. One layer can communicate with an adjacent layer by using its interface.OSI model was advanced by ... Read More

To separate a particular portion from the image, we have to locate the area first. Then we have to copy that area from the main image to another matrix. This is how the ROI in OpenCV works.In this example, two matrices have been declared at the beginning. After that, an ... Read More

We have declared three variables named-'blue_Channel', 'green_channel' and 'red_channel'. The goals of these variables is to save the pixel values. We have used these variables inside the 'for loops'. Then we declared a matrix named 'color_Image_Matrix'.The syntax of this method is:blue_Channel = color_image_Matrix.at(i, j)[0];We used a BGR image. It has ... Read More

Here, we will learn how to detect and track the motion of eyeball in OpenCV.The following program demonstrates to detect the eyeball and track the location.Example#include #include #include #include #include #include using namespace cv; using namespace std; Vec3f eyeBallDetection(Mat& eye, vector& circles) {    vectorsums(circles.size(), 0);    for (int y ... Read More

Here, we will learn how to track the eye in OpenCV. After detective the eyes, the tracking is an effortless and straightforward task. We used the circle to enclose the detected eyes. Tracking the center of the circle means tracking the center of eyes. To track the center of the ... Read More

Here, we will learn how to detect the eye in OpenCV. We will use haarcascade_eye.xml classifier located in 'C:/opencv/sources/data/haarcascades' to detect the eyes. To detect the eyes, we need to add these headers.The first header is , and it is the header of C++ programming language. Reading writing images and ... Read More