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Top 10 applications of Image processing

Mon May 17 2021  ·  

AI

 ·  5 min read
Digital Image Processing
Introduction

Living in the millennial's time, visual interpretations have become an integral part of communication. With the introduction of image editing and capturing applications in the market, the demand for better image quality has increased. But are the images restricted to just flaunting? NO! Let us explore the top 10 image processing applications.

 

What are image processing applications?

The applications used by a digital computer to process digital images via an algorithm are known as Digital Image processing. The taken image is then used in executing computer functions to derive an enriched version of the same or obtain the desired information from it.

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Top 10 Image processing applications

With the ever-growing technology, digital image processing applications are penetrating almost all fields at a very fast rate. Let us explore the various factors where digital image processing applications are used.

1) Image polishing and restoration

The process by which we can alter the look and feel of an image. It fundamentally manipulates the images and helps to achieve the desired output. It includes conversion, sharpening, blurring, detecting edges, retrieval, and recognition of images.

2) Medical Field

There are several applications in the medical field which depend on the functioning of digital image processing. Many methods are used such as segmentation and texture analysis, which are further used for cancer and other disorder identifications.

image recognition in medical field

Medical image processing incorporates the use and exploration of 3D image datasets of the human body, found generally from a Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scanner. It further helps to diagnose pathologies or steer medical interventions such as surgical planning, or for research purposes. Gamma-ray imaging, PET scan, X-Ray Imaging, Medical CT scan, and UV imaging are a few medical image processing applications. 

3) UV Sensing

With the progress in technology, the use of remote sensing has become increasingly common and in great demand within the domain of natural hazards. The increase of geospatial technology and the advantage to provide recent and accurate imagery to the public through the advances of technology and the internet.

The area of the earth is inspected by a satellite or from high grounds and then it is analyzed to obtain information in the field of remote sensing. One of the best applications of digital image processing in the field of remote sensing is to detect infrastructure damages caused by an earthquake. The key steps in the analysis include the extraction of edges and the Analysis and enhancement of various types of edges.

Since the area affected by the earthquake is sometimes so widespread, that is not possible to examine the damage with the human eye. Further, it will be a very hectic and time-consuming procedure. Therefore, comes digital image processing to the rescue as it captures an image from above the ground and then helps in the analysis of damage and further actions being taken quickly.

4) Transmission and encoding

Today with the advancement of technology, we can see live video feeds, or live CCTV footage from any part of the world within a matter of seconds. This means that not only transmission but encoding of images has improved by multiple folds. A variety of formats have been developed for high or low bandwidths to encode images and then stream them over the internet.

Transmission in digital image processing is obtaining an image in microscopy which shows the intensity of light, or any radiation that has come through the sample and they are generated by techniques such as light microscopy or transmission electron microscopy. Furthermore, image compression deals with lowering the amount of data required to represent a digital image by deleting unnecessary data, so that the digital image processing is complete, and the image is fit to be sent across.

5) Robot vision

Robot Vision entails using a combination of camera hardware and computer algorithms that allow robots to process visual data from the world. Several robotic machines work on digital image processing. Through image processing technique robot finds their way. Without digital image processing in Robots, it is essentially blind.

Robot vision

Robots use vision to carry out advanced tasks in an environment that is constantly changing. The technology of digital cameras is extremely advanced, and they can relocate high-resolution pixel arrays to the robot's computer. Algorithms for digital image processing augment and interpret these images.

Nowadays, it is vital to make the robot able to see things, identify any hurdles, and allow humans to make the most of the technology and digital image processing.

Also read: Everyday Usage of Image Recognition

6) Pattern recognition

pattern recognition

Presently, image processing is used for image recognition patterns and to give human recognition intelligence to the machine which is required in image processing. Pattern recognition is useful to extricate significant features from image/video samples. It is further used in computer vision for numerous applications like biological and biomedical imaging. When combined with artificial intelligence such that computer-aided diagnosis, handwriting recognition, and image recognition can be easily applied.

7) Video processing

Video processing is a collection of frames or pictures that are arranged such that it creates quick movements. It includes frame rate conversion, motion detection, reduction of noise, and colour space conversion.

Video processing is a unique case of signal processing, in particular image processing, which often utilizes video filters and where the input and output signals are video files or video streams. Video processing techniques are commonly used in television sets, VCRs, DVDs, video codecs, video players, video scalers, and other devices.

Also, check our Cognitive Image Processing services.

8) Hurdle detection

Hurdle detection is one of the ordinary tasks that has been done through image processing, by detecting the different types of objects in the image and then estimating the distance between the robot and the hurdles. It is done simply using the camera sensor and with the knowledge of image processing.

9) Line follower robot

Most of the robots today work by following the line and thus are called line follower robots. A line-following robot is a computerized device programmed to follow a specific path with the help of digital image processing. Some existing practices used in controlling line-following robots are IR sensors, LDR sensors, etc. This helps a robot to move on its path and perform some tasks.

10) Color processing

A digital colour image includes colour information for every pixel. A colour image has three values per pixel, and they calculate the intensity and chrominance of light. The information stored in the digital image data is the brightness information in each shadowy band. It further involves studying the transmission, storage, and encoding of these colour images.

Conclusion

Digital image processing comes in handy with a lot of advantages in times of today allowing humans to make the most of technology and with visual representations.

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