In the modern world, Image Processing is a widely growing technology which is used to improve image quality by applying mathematical operations and modifying characteristic parameters related to digital images. It forms the core area in the research field of engineering and computer science disciplines. Image processing is a type of signal processing where the input and outputs are images or features associated with the idea. It has extensive applications in many areas including astronomy, medicine, robotics, remote sensing and so on.
Image Processing is a technique to improve raw images received from cameras or sensors placed on satellites, space probes and aircraft or pictures taken in everyday life for various applications. Various techniques have been developed in Image Processing during the last five decades.
Image processing requires fixed sequences of operations that are performed at each pixel of an image. The image processor performs the first sequence of operations on the image, pixel by pixel. Once this is entirely done, it will begin to complete the second operation, and so on. The output value of these operations can be computed at any pixel of the image.
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Image processing is a type of signal processing. It is the process of transforming an image into a digital form and performing certain operations to get an enhanced image or extract some useful information from it. In image processing, all images are usually considered 2D signals when applying certain predetermined signal operations.
Digital Image Processing means processing digital images by use of computer algorithms, in order to get enhanced images or to extract some useful information. These algorithms may vary according to the desired output image.
Types Of Image Processing
There are two basic types of Image processing
Analog Image Processing
Analog Image Processing refers to the alteration of the image through electrical means. The most common example is the television image. This technique is used for hardcopies like Printouts, Photographs, Paintings, X-rays, Medical Images, etc.
In analog signal processing, the signals are two-dimensional, thus various fundamental Interpretations are used by Image Analytics. The images are manipulated by electrical signals that are time-varying.
Digital Image Processing
This technique is used in the manipulation of digital images by using computers. Digital image techniques are mainly classified into three categories.They are
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Functions of Image Processing
The five main functions of image processing technique are
is the process of recognizing or identifying and comprehending images more effectively and subsequently improving performance in judgements and decisions.
The ability to distinguish and identify an object from a cluster of objects and to describe it in detail.
The process that helps to highlight and enhance fine details that are present in the image by removing blur and haziness.
It is the ability to recognize certain patterns and then identify the images that contain those patterns.
The process of retrieving obscured images from the database of digital images as per the requirements.
Steps in Image Processing
There are 10 important techniques or steps used in processing images. The Image Processing Steps are as follows:
Image acquisition is the first step in image processing. This is also known as preprocessing in image processing. This involves retrieving the image from a hardware-based source, especially from a source.
Image enhancement is the process of improving and highlighting certain features of interest in an image for clarity. This involves changing the brightness, contrast, blurriness, opaqueness, transparency etc.
Image Restoration is fascinating since advanced techniques could potentially restore damaged historical documents. Powerful Deep Learning-based image restoration algorithms are used to reveal zillions of missing information from unclear records.
Colour Image Processing
This process has gained dominance due to the significant use of digital images over the internet. Colour image processing includes a number of colour modelling techniques in the digital domain.
Wavelets and Multiresolution Processing
Wavelets are used to represent images in various degrees of resolution. The images are subdivided into wavelets or smaller regions for data compression and for pyramidal representation.
Compression is a process that minimizes the space to store an image or the bandwidth required to transmit it. Especially, when the image is for use on the Internet.
Morphological processing is a set of processing techniques used for changing the shapes of images. It aims to remove these imperfections by accounting the form and structure of the image.
Image Segmentation involves partitioning an image into its constituent parts/ objects. Different key parts simplify and change the representation of an image to be more meaningful and easier to analyze.
After an image is segmented, each region is represented and described in a form suitable for further computer processing. Representation deals with the image’s characteristics and regional properties.
Description deals with extracting quantitative information that helps differentiate one class of objects from the other. Image description conveys information to the visually impaired. Alt-text and Long descriptions are two types.
Advantages of Image Processing
In the technical field, image processing techniques and their implementation have a wide impact. Some of the common benefits of image processing, regardless of the field of operation are mentioned here:
The digital image can be made available in any desired format such as .jpeg, .img, X-Ray, photo negative, etc.
It helps to improve the image in human interpretation such as biometric identification.
For machine interpretation the information can be processed and extracted from images.
Since the images are made of pixels, they can be manipulated to any desired density and contrast.
By using image processing the images can be stored, retrieved and transmitted easily at any time from anywhere.
20+Topics in Image Processing Projects
Forgery Detection Of Medical Image
Text Recognition In Images by Python
Driver Sleepiness Detection Using Python
Face Detection Using Python
Erosion & Detection Using Python
Cartooning Of Images Using Python
Monitoring of Volcano Using Embedded ARM in Remote Areas
Protection Of Multimedia Through Content & Fingerprints
Controlling pests in Agriculture Field using Image processing
Verification of Signature using Matlab
Detection of kidney Stone Using Matlab
Recognition Of License Plate Through Image Processing
Identification of Disease in Plant Leaf
Mixed Convolution & Network-Based Recognition Of Eye
Recognition of Face Emotion in Real-Time Using Matlab
Smart Farming System Using IoT and Android
Human Act Identification Through Image Processing
Automatic Parking Of Vehicles using Image Processing
Rice grains Grading through Image Processing
Image Processing Based Controlling Of Intelligent Traffic Lights
Biometric Recognition System Through Image Processing
Classification of Flowers Through Image Processing
Medical Image Segmentation Using Image Processing
Currency Identification System using Image Processing
Image Processing-Based Tracking and Counting Vehicles
Quilting Images And Synthesising Textures
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Applications of Image processing
We could often wish to make old images better. And that is possible through image processing. Techniques like Zooming, sharpening, edge detection, and high dynamic range editing all fall under this category. All these steps help in enhancing the images. Most editing apps use this technology for correcting images.
Filters on Editing Apps and Social Media
Editing apps and social media apps provide filters which make the image look more appealing. These Filters are usually a set of functions of image processing that change the colours and other aspects in an image that make the image look different. Filters are an interesting application for Image processing and are mostly used.
In the medical field, Image Processing is used for various tasks like scanning, X-Ray Imaging, UV imaging, Cancer Cell Image processing, and much more. The introduction of Image Processing to the medical technology field has greatly improved the diagnostics process. The processed image should be very clear and can be used for better diagnostics. Medical imaging is used for producing images of the internal structures of a body.
Computer / Machine Vision
One of the most interesting applications of Image Processing is Computer Vision. It makes the computer see, identifies things, and process the whole environment. Some of the important use of Computer Vision is Self Driving cars, Drones, obstacle detection, path recognition, and understanding the environment for Car Autopilots. The computer takes live footage and analyses traffic on the road and other obstacles.
Pattern recognition is a part of Image Processing that involves Artificial Intelligence and Machine Learning algorithms. Image processing is used to find out various patterns and various aspects of images. Pattern Recognition technique is used for Handwriting analysis, Image recognition, Computer-aided medical diagnosis, Biometric Identification and much more.
Video is the fast movement of a stream of images. Various image processing techniques are utilized in Video Processing. Some methods of Video Processing are noise removal, image stabilization, frame rate conversion, detail enhancement, and much more. Thus Image processing plays a vital role in video processing.
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