Basics of Digital Image Processing
Use of DIP in Society
Digital Image Processing Process
Why do we process images?
Image Enhancement and Edge detection
Python
How are we using Python in DIP
This document provides an overview of digital image processing. It discusses key concepts like image sampling, quantization, and the fundamental steps in digital image processing such as image acquisition, enhancement, restoration, and representation. The document also outlines the objectives and units of a digital image processing course, which covers topics like image fundamentals, enhancement, restoration, segmentation, wavelets, compression, and image recognition. Applications of digital image processing discussed include remote sensing, medical imaging, and robotics.
This document provides an overview of digital image processing. It discusses key concepts like image types (intensity, binary, indexed, RGB), image file formats (TIFF, JPEG), image resolutions, and the steps involved in digital image processing. The MATLAB Image Processing Toolbox is also mentioned as a tool for performing operations on images like visualization, analysis, and processing. Edge detection is highlighted as an important but difficult task in digital image processing.
Computer vision is a field that deals with how computers can understand digital images and videos. It seeks to automate tasks that the human visual system can perform, such as object recognition. One example is computer vision systems in self-driving cars that can identify objects on the road to help drivers or prevent collisions. Computer vision involves various image processing levels from low-level tasks like noise removal to high-level tasks like scene understanding. Digital images come in various types like binary, grayscale, and color images represented by different numbers of bits per pixel.
Lesson 6 discusses images in multimedia. It covers creating still images using bitmaps or vector graphics. Bitmaps use pixels to represent images while vector graphics use mathematical formulas. The document also discusses color models like RGB and HSB. Color palettes define the available colors and dithering is used to match colors. Common file formats for images on different platforms are also presented.
Images are an important element in multimedia. There are two main types of images: bitmaps, which use pixels to represent color information, and vector images, which use mathematical coordinates. Various tools can be used to create and edit images, including bitmap software, 3D modeling programs, and image capture and editing features. Color is a key aspect, with different color models and palettes used depending on the intended display and use of the images.
This document summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They are easy to create but large in file size. Vectors use mathematical expressions to represent shapes and objects and are smaller in file size, but more difficult to create. Factors like compression and resolution can impact image quality. Both scanning and digital photography are discussed as methods to capture images, each with advantages and disadvantages. Common file formats, programs used, and organizing digital assets are also summarized.
This document provides an overview of computer graphics and its applications. It discusses various types of video display devices used in computer graphics like CRTs and flat panel displays. It describes how raster scan and random scan systems work and lists common input and output devices. The document outlines different chapters that will cover topics like line and curve generation algorithms, transformations, 3D viewing, surface detection, and modeling techniques. It provides examples of how computer graphics is used in fields like CAD, presentations, entertainment, education, visualization, image processing, and graphical user interfaces.
This document provides an overview of digital image processing. It discusses key concepts like image sampling, quantization, and the fundamental steps in digital image processing such as image acquisition, enhancement, restoration, and representation. The document also outlines the objectives and units of a digital image processing course, which covers topics like image fundamentals, enhancement, restoration, segmentation, wavelets, compression, and image recognition. Applications of digital image processing discussed include remote sensing, medical imaging, and robotics.
This document provides an overview of digital image processing. It discusses key concepts like image types (intensity, binary, indexed, RGB), image file formats (TIFF, JPEG), image resolutions, and the steps involved in digital image processing. The MATLAB Image Processing Toolbox is also mentioned as a tool for performing operations on images like visualization, analysis, and processing. Edge detection is highlighted as an important but difficult task in digital image processing.
Computer vision is a field that deals with how computers can understand digital images and videos. It seeks to automate tasks that the human visual system can perform, such as object recognition. One example is computer vision systems in self-driving cars that can identify objects on the road to help drivers or prevent collisions. Computer vision involves various image processing levels from low-level tasks like noise removal to high-level tasks like scene understanding. Digital images come in various types like binary, grayscale, and color images represented by different numbers of bits per pixel.
Lesson 6 discusses images in multimedia. It covers creating still images using bitmaps or vector graphics. Bitmaps use pixels to represent images while vector graphics use mathematical formulas. The document also discusses color models like RGB and HSB. Color palettes define the available colors and dithering is used to match colors. Common file formats for images on different platforms are also presented.
Images are an important element in multimedia. There are two main types of images: bitmaps, which use pixels to represent color information, and vector images, which use mathematical coordinates. Various tools can be used to create and edit images, including bitmap software, 3D modeling programs, and image capture and editing features. Color is a key aspect, with different color models and palettes used depending on the intended display and use of the images.
This document summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They are easy to create but large in file size. Vectors use mathematical expressions to represent shapes and objects and are smaller in file size, but more difficult to create. Factors like compression and resolution can impact image quality. Both scanning and digital photography are discussed as methods to capture images, each with advantages and disadvantages. Common file formats, programs used, and organizing digital assets are also summarized.
This document provides an overview of computer graphics and its applications. It discusses various types of video display devices used in computer graphics like CRTs and flat panel displays. It describes how raster scan and random scan systems work and lists common input and output devices. The document outlines different chapters that will cover topics like line and curve generation algorithms, transformations, 3D viewing, surface detection, and modeling techniques. It provides examples of how computer graphics is used in fields like CAD, presentations, entertainment, education, visualization, image processing, and graphical user interfaces.
This document discusses digital graphics, including bitmap and vector images. Bitmaps are made up of pixels and cannot be scaled up without losing quality, while vectors are made of points, lines and curves and can be scaled without losing clarity. The document also examines factors that affect image quality like compression, and how images can be captured through scanning, digital cameras, or drawing. Output and storage of images depends on the file type and size.
This report summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They are easy to create but large in file size. Vectors use mathematical expressions to represent shapes and are smaller in file size, but harder to create. They are best for logos, icons, and drawings. The report discusses advantages and disadvantages of each, as well as factors that affect quality like resolution and compression. It also covers capturing images through scanning and photography and organizing assets for projects.
This report summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They allow for realistic images but large file sizes. Vectors use mathematical expressions to represent shapes and objects, allowing for scalability and smaller file sizes but requiring more time and skill. Both have advantages for certain uses, and quality can be affected by compression, resolution, and how images are captured through scanning or photography. Proper organization of graphic files is also discussed.
This report summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They allow for realistic images but large file sizes. Vectors use mathematical expressions to represent shapes and graphics like logos. They are scalable, with small file sizes but require more time and skill to create. Both have advantages and disadvantages depending on the intended use of the graphic. The report also discusses factors that affect quality like resolution and compression, and methods for capturing images digitally through scanning or photography.
This report summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photographs with many colors. They allow for realistic images but large file sizes. Vectors use mathematical expressions to represent shapes and graphics like logos. Vector files are smaller and allow for smooth scaling but require more time and skill to create. Both file types have advantages and disadvantages depending on the intended use and output of the digital graphic. The report also discusses factors like resolution and compression that impact image quality.
This document discusses digital graphics, including bitmap and vector images. Bitmaps are made up of pixels and cannot be scaled up without losing quality, while vectors are made of points, lines and curves and can be scaled without losing clarity. The document also covers factors that affect image quality like compression, different ways of capturing images such as with a camera or scanner, and how images are output and stored.
Computer graphics Applications and System OverviewRAJARATNAS
Computer graphics deals with the creation, manipulation, and storage of digital images and objects. It has many applications including computer art, computer-aided design, presentations, entertainment, education, training, visualization, image processing, and machine drawing. A graphics system consists of graphics hardware like the GPU, video card, display, and input devices, as well as graphics software like drivers, APIs, modeling/animation tools, libraries, and game engines. It uses a rendering pipeline to process graphics from 3D models into 2D pixels for display.
The document discusses graphics and their importance in integrative media, describing different types of graphics like raster images, vector images, and factors that affect graphic quality like size, color depth, and resolution. It also outlines some graphic file formats, software used for creating and editing graphics, and color models like RGB, CMYK, and HSB.
This document discusses the basics of computer graphics. It outlines the advantages of computer graphics such as producing high quality images and animation. It also classifies computer graphics systems as either interactive or passive. Interactive systems allow two-way communication between the user and computer while passive systems do not. The document then discusses pixels, color depth, frame buffers, and monitors. It concludes by outlining major areas of computer graphics like display of information, design/modeling, simulation, and user interfaces.
This document discusses graphics and multimedia technology. It covers various topics related to graphics including different types of images (raster/bitmap and vector), color, file formats, and methods for obtaining images. Specifically, it describes raster images as composed of pixels and matrices, while vector images use objects like lines and shapes. It also discusses color palettes, resolution, dithering, and scanning, digitizing, and capturing images using cameras, scanners, and software tools.
The document discusses digital image processing and provides details on key concepts. It begins with an overview of digital image fundamentals such as image sampling and quantization. Next, it describes the components of an image processing system including image sensors, hardware, software, displays and storage. Finally, it covers topics such as image formation in the eye, brightness adaptation, and the representation of digital images through sampling and quantization.
The document discusses a computer vision workshop that covered topics including what a digital image is, what digital image processing is, examples of digital image processing, and key stages in digital image processing. It defines a digital image as a finite set of pixels representing properties like gray levels or color. Digital image processing focuses on improving images for interpretation and processing images for storage, transmission and machine perception. Examples covered include image enhancement, medical imaging, geographic information systems, law enforcement, and object segmentation. Key stages discussed include image acquisition, restoration, enhancement, representation and description, segmentation, and compression.
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Face detection is an important part of computer vision and OpenCV provides algorithms to detect faces in images and video. The document discusses different face detection methods including knowledge-based, feature-based, template matching, and appearance-based. It also covers how to set up OpenCV in Python, read and display images, extract pixel values, and detect faces using Haar cascades which use Haar-like features to train a classifier to identify faces. Future applications of face detection with OpenCV include attendance systems, security, and more.
This document provides an overview of computer graphics and its applications. It defines computer graphics as the creation and manipulation of geometric objects and images through computer programs. Some key applications discussed include:
- Computer-aided design (CAD) for modeling objects like buildings, vehicles, and products.
- Presentation graphics for illustrating data through charts, graphs, and diagrams.
- Entertainment applications like movies, games, and animation through modeling and rendering techniques.
- Education and training through interactive models of systems.
- Visualization of scientific and business data.
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This document discusses graphics and their use in multimedia applications. It defines graphics as pictures, diagrams, charts and backgrounds. It discusses resolution and color depth of graphics. The two main types of graphics are vector graphics, which are represented by geometric shapes, and bitmap graphics, which are represented by pixels in an array. Bitmap graphics have higher image quality but larger file sizes than vector graphics. The document also covers compression formats, image sizes, sources of graphics, and software used to create and edit graphics.
This document discusses desktop basics related to graphics file formats, resolution, image size, colors, and image compression. It defines graphics file formats as sets of standards for organizing and storing digital pictures using uncompressed, compressed lossless or lossy, or vector data. Resolution refers to the quality, sharpness, and clarity of an image, measured by dots per inch for printers or pixels for screens. Image size is influenced by the number of pixels and color depth, with higher quality images having more pixels and colors. Common color pixels include 8-bit (256 colors) and 24-bit (16 million colors, known as true color). Image compression techniques decrease image file size using lossy or lossless methods to reduce storage needs and speed
Computer graphics involves the generation and manipulation of images using computers. It has applications in design, simulation, entertainment, education and presentations. A computer graphics system typically includes input devices like mice and touchscreens, processing hardware and memory, and visual output displays. Key concepts in computer graphics include pixels, which make up images, and resolution, the number of pixels that can be displayed. Common uses of computer graphics are computer-aided design for engineering drawings, data visualization, animation and special effects in movies and games.
I. The key applications of computer graphics discussed in the document are education and training, entertainment, computer-aided design, graphs and charts, virtual reality, data visualization, computer art, image processing, and graphical user interfaces.
II. The document provides an overview of graphics systems, discussing raster-scan displays and random-scan displays. Raster-scan displays use a frame buffer to store pixel values and refresh the screen in a series of horizontal lines, while random-scan displays directly address pixels.
III. Interactive graphics systems consist of a display controller, frame buffer, and monitor. The display controller determines images from user input and stores them in the frame buffer. The monitor displays the frame buffer contents refreshed
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This document discusses digital graphics, including bitmap and vector images. Bitmaps are made up of pixels and cannot be scaled up without losing quality, while vectors are made of points, lines and curves and can be scaled without losing clarity. The document also examines factors that affect image quality like compression, and how images can be captured through scanning, digital cameras, or drawing. Output and storage of images depends on the file type and size.
This report summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They are easy to create but large in file size. Vectors use mathematical expressions to represent shapes and are smaller in file size, but harder to create. They are best for logos, icons, and drawings. The report discusses advantages and disadvantages of each, as well as factors that affect quality like resolution and compression. It also covers capturing images through scanning and photography and organizing assets for projects.
This report summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They allow for realistic images but large file sizes. Vectors use mathematical expressions to represent shapes and objects, allowing for scalability and smaller file sizes but requiring more time and skill. Both have advantages for certain uses, and quality can be affected by compression, resolution, and how images are captured through scanning or photography. Proper organization of graphic files is also discussed.
This report summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photos with many colors. They allow for realistic images but large file sizes. Vectors use mathematical expressions to represent shapes and graphics like logos. They are scalable, with small file sizes but require more time and skill to create. Both have advantages and disadvantages depending on the intended use of the graphic. The report also discusses factors that affect quality like resolution and compression, and methods for capturing images digitally through scanning or photography.
This report summarizes different types of digital graphics, including bitmaps and vectors. Bitmaps are composed of pixels and are best for photographs with many colors. They allow for realistic images but large file sizes. Vectors use mathematical expressions to represent shapes and graphics like logos. Vector files are smaller and allow for smooth scaling but require more time and skill to create. Both file types have advantages and disadvantages depending on the intended use and output of the digital graphic. The report also discusses factors like resolution and compression that impact image quality.
This document discusses digital graphics, including bitmap and vector images. Bitmaps are made up of pixels and cannot be scaled up without losing quality, while vectors are made of points, lines and curves and can be scaled without losing clarity. The document also covers factors that affect image quality like compression, different ways of capturing images such as with a camera or scanner, and how images are output and stored.
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Computer graphics deals with the creation, manipulation, and storage of digital images and objects. It has many applications including computer art, computer-aided design, presentations, entertainment, education, training, visualization, image processing, and machine drawing. A graphics system consists of graphics hardware like the GPU, video card, display, and input devices, as well as graphics software like drivers, APIs, modeling/animation tools, libraries, and game engines. It uses a rendering pipeline to process graphics from 3D models into 2D pixels for display.
The document discusses graphics and their importance in integrative media, describing different types of graphics like raster images, vector images, and factors that affect graphic quality like size, color depth, and resolution. It also outlines some graphic file formats, software used for creating and editing graphics, and color models like RGB, CMYK, and HSB.
This document discusses the basics of computer graphics. It outlines the advantages of computer graphics such as producing high quality images and animation. It also classifies computer graphics systems as either interactive or passive. Interactive systems allow two-way communication between the user and computer while passive systems do not. The document then discusses pixels, color depth, frame buffers, and monitors. It concludes by outlining major areas of computer graphics like display of information, design/modeling, simulation, and user interfaces.
This document discusses graphics and multimedia technology. It covers various topics related to graphics including different types of images (raster/bitmap and vector), color, file formats, and methods for obtaining images. Specifically, it describes raster images as composed of pixels and matrices, while vector images use objects like lines and shapes. It also discusses color palettes, resolution, dithering, and scanning, digitizing, and capturing images using cameras, scanners, and software tools.
The document discusses digital image processing and provides details on key concepts. It begins with an overview of digital image fundamentals such as image sampling and quantization. Next, it describes the components of an image processing system including image sensors, hardware, software, displays and storage. Finally, it covers topics such as image formation in the eye, brightness adaptation, and the representation of digital images through sampling and quantization.
The document discusses a computer vision workshop that covered topics including what a digital image is, what digital image processing is, examples of digital image processing, and key stages in digital image processing. It defines a digital image as a finite set of pixels representing properties like gray levels or color. Digital image processing focuses on improving images for interpretation and processing images for storage, transmission and machine perception. Examples covered include image enhancement, medical imaging, geographic information systems, law enforcement, and object segmentation. Key stages discussed include image acquisition, restoration, enhancement, representation and description, segmentation, and compression.
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This document provides an overview of computer graphics and its applications. It defines computer graphics as the creation and manipulation of geometric objects and images through computer programs. Some key applications discussed include:
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Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
YCIS_Forensic PArt 1 Digital Image Processing.pptx
1. “Digital Image Processing using Python”
Dr. Sharmila S. More
Assistant Professor
Department of Computer Science
MIT Art's Commerce and Science College Alandi (D),Pune-15
2. Topics to be Covered…
Basics of Digital Image Processing
Use of DIP in Society
Digital Image Processing Process
Why do we process images?
Image Enhancement and Edge detection
Python
How are we using Python in DIP
3. What is Digital Image Processing
Digital Image Processing means processing digital image by means of a digital
computer
Image processing mainly include the following steps:
1.Importing the image via image acquisition tools;
2.Analysing and manipulating the image;
3.Output in which result can be altered image or a report which is based on analysing
that image.
Image Processing System is the combination of the
different elements involved in the digital image
processing.
Digital image processing is the processing of an image
by means of a digital computer.
Digital image processing uses different computer
algorithms to perform image processing on the digital
images.
4. What is an image?
In other words, an image can be defined by a two-dimensional array specifically arranged in rows and columns.
Image is
Digital Image is composed of a finite number of elements, each of which elements have a particular value at a particular
location. These elements are referred to as picture elements,image elements,and pixels.A Pixel is most widely used to denote
the elements of a Digital Image.
There are two types of methods used for image processing namely, analog and digital image
processing.
•Analog image processing can be used for hard copies like printouts and photographs.
•Digital image processing techniques help in the manipulation of digital images by using
computers.
•A two-dimensional array of numbers(or pixels) ranging between 0 and 255.
•It is defined by the mathematical function f(x,y) where x and y are the two co-ordinates horizontally and vertically.
The range of the colors in 8 bit vary from 0–255 where:
•0 — black
•255 — white
•127 — gray color.
5. Types of an image
1. BINARY IMAGE– The binary image as its name suggests, contain only two pixel elements i.e 0 & 1,where
0 refers to black and 1 refers to white. This image is also known as Monochrome.
2. BLACK AND WHITE IMAGE– The image which consist of only black and white color is called BLACK
AND WHITE IMAGE.
3. 8 bit COLOR FORMAT– It is the most famous image format.It has 256 different shades of colors in it and
commonly known as Grayscale Image. In this format, 0 stands for Black, and 255 stands for white, and 127
stands for gray.
4. 16 bit COLOR FORMAT– It is a color image format. It has 65,536 different colors in it.It is also known as
High Color Format. In this format the distribution of color is not as same as Grayscale image.
A 16 bit format is actually divided into three further formats which are Red, Green and Blue i.e. RGB.
6. Image as a Matrix
As we know, images are represented in rows and columns we have the following syntax in which images are
represented:
The right side of this equation is digital image by definition. Every element of this matrix is called image element
, picture element , or pixel.
7. Why do we process images?
It has been developed to deal with 3 major problems —
•To improve the image data to suppress the unwanted distortions.
•To enhance some features of the input image.
•As a means of translation between the human visual system and digital imaging devices.
9. 1) Image Acquisition: capturing an image 2) Image Enhancement: filtering image, to improve the quality.
3)Image Restoration: improving
appearance (reducing blurring etc) of an image
by mathematical or probabilistic models.
4)Colour Image
Processing: use of the digital
image has increased.
10. 5) Multi-Resolution Processing: It is the process of representing images in various degrees of resolution.
6) Compression: It involves the techniques for reducing the size of the image with minimum deterioration in its quality.
7) Morphological Processing: It is the
process for extracting image
components that are useful in
the representation and description
of shape.
11. 8) Segmentation: It is the
process of partitioning the
image into multiple
segments.
9) Representation and Description:
It involves representing an image in various forms:
Boundary Representation — It focuses on the external shape characteristics such as corners and inflections.
Regional Representation — It focuses on internal properties such as texture and skeletal shape.
12. 10) Feature Matching: We can extract the same features from a different image of the same cathedral taken from a different
angle.
11) Recognition: It is the process
of assigning labels to an object based
on its description.
13. How are we using Programming Languages
Computer programming is the process of writing code to
facilitate specific actions in a computer, application or
software program, and instructs them on how to perform.
Computer programmers are professionals that create
instructions for a computer to execute by writing and
testing code that enables applications and software
programs to operate successfully.
14.
15. There are thousands of programming languages in the world now due to technology evolution and innovation.
Programmers can choose which one they want according to the kind of job they need to complete.
•For Application and Program Development – C, C#, C++, D, Java, Swift, and Tcl.
•For Artificial intelligence development – AIML, C, C#, C++, Prolog, and Python.
•For Database development – DBASE, FoxPro, MySQL, SQL, and Visual FoxPro.
•For Game development – C, C#, C++, DarkBASIC, and Java.
•For Computer drivers – Assembly and C.
•For Internet and web – HDML, HTML, Java, JavaScript, Perl, PHP, Python, and XML.
•For Script development – AutoHotkey, awk, bash, Batch file, Perl, Python, and Tcl.
Programming language is the way by which programmers communicate with computers.
They are mostly a set of instructions that they give to the computer for completing a certain task.
For example –
They are essential for developing applications and websites
16. Who uses programming languages?
Computer programmers use programming languages to code website functions, edit the appearance of web pages
and organize data. Some jobs that use programming languages include the following professionals:
Web developer: This role is responsible for designing the structure and database of a website.
Web designer: The visual and interactive features of websites are programmed by this professional.
Video game developer: This type of software developer specializes in the design and creation of video games
using coding for graphics and interactivity.
Computer systems engineer: An individual in this occupation develops and tests software for personal
computers.
Software quality assurance engineer: This quality assurance professional oversee the development process
for software function and design.
App developer: This type of programmer designs and creates applications for computers or mobile devices.
Popular Programming Languages
17. Why We Need Programming
Programming helps automating lot
of time consuming activities and
reduces the human errors.