Image Processing — In Recent Years
By: Vidhi Raghvani
Tags: Image Processing, Robotics, Neural Networks, Machine Vision, Artificial Intelligence

Image Processing is a rapidly developing field with innovative technologies being developed at an astounding rate. Through this blog, we would delve into the world of Image Processing and Machine Vision applications to highlight some of the emerging technologies that might have gone unnoticed in recent years.

CASHIER-LESS STORES

Amazon GO is a concept grocery store, where users do not have to interact with any cashiers or staff. They simply walk in, put items in their basket, and walk out. The stores use an immense array of ceiling-mounted cameras to track users and the products they purchase. Currently, in development with only 26 stores in 4 major US cities, they are expected to expand worldwide very soon.

2. AUGMENTED REALITY

Retailers like Lenskart and Snapchat offer augmented reality services where a user can view products using augmented reality before they purchase them. In the case of Lenskart, it projects a 3D model of its spectacles onto the user’s face which can be viewed from multiple angles, allowing a user to virtually try the product in the comfort of their own home.

3. OPTICAL CHARACTER RECOGNITION

OCR is a technology that is so widespread today, we take it for granted and almost forget its association with machine vision and artificial intelligence. It enables systems to recognize alphanumeric characters and convert them to computer-format text.

4. VIDEO GAMES

Even in the field of video games, advances are being made due to the introduction of image processing and machine vision. Popular games “NBA2k19” and “WWE20” allow players to upload a photo of their face, which is then applied to character models in-game.

5. ROBOTICS: IDENTIFICATION, GAUGING AND INSPECTION

Guidance — Machine systems can determine the location, position and orientation of a given part, and can be used to correct any misalignments. This method achieves far greater speed and accuracy when compared to humans performing the same task.

Identification — An image processing system can read barcodes (1D), data matrix codes (2D), direct part marks (DPM) and OCR, alphanumeric characters as well. The development of these systems have enabled compact data storage techniques for products

Gauging — A machine vision system calculated the distance between two defined marks and determines if those marks meet design specifications or not. This is a core application in the field of instrumentation as it enables the high precision gauging of instruments.

Inspection — Machine Vision systems can scan a product of defects, irregularities, flaws, and contaminants and take suitable action without human interference. They can also inspect a product for completeness and tampering

6. DRONE TECHNOLOGY

DJI, the world’s leading manufacturer of commercial hobbyist drones, have integrated machine vision features in their latest product, the DJI Phantom 4. It utilizes two forward-facing and two downward-facing optical sensors along with two dedicated image processors to determine its location by comparing the scene from multiple vantage points. This system allows it to locate itself with exceptional accuracy outdoors and allows it to fly indoors without a GPS signal.

These sensors give the drone a 60° by 50° field of view, while normal ultrasonic sensors only provide 15°. This enhanced field of view allows the drone to detect obstacles in its path and maneuver around them. In the event of an obstacle entering its operating area suddenly, the drone can immediately halt and fly away.

7. AUTONOMOUS VEHICLES

It’s no secret autonomous vehicles use a wide variety of techniques to perform at the level they currently do. However, we mustn’t forget that at the root of companies like Tesla, Ford and Audi, machine vision is the core component of the systems that allow the cars to safely and automatically navigate lanes, read signs, stop for traffic lights, and so much more.

Tesla

8. SECURITY SYSTEMS

Image Processing and Machine vision systems can be paired with Convolutional Neural Networks to perform facial recognition as a biometric identification component to authorize personnel for highly sensitive workspaces.

9. MOBILE PHONE TECHNOLOGY, ENHANCED PHOTOGRAPHY

Multiple smartphone manufacturers are implementing AI-based machine vision systems into their camera applications, which offer a myriad of possibilities in terms of features.

Google’s Pixel 3, for example, introduced a “portrait mode” which recognizes human subjects and blurs the background, giving the photo a professional look.

Google is also developing “Super Res Zoom” and “Night Sight”, which use machine vision to offer enhanced zoom levels and low light picture options, respectively.

10. QR CODE DETECTION

Mobile applications like PayPal and Google Pay make use of QR codes for online payments, due to their advantage of facilitating instant payment features. The main reason for implementing the use of QR codes into a payment platform is done due to its extreme security. Any sort of data transferred through a quick response code is highly encrypted and all one has to do is scan the particular code and confirm payment. E-ticket booking, fuel retailing, parking payments, and micro-businesses are a few of the many real-world applications that make use of the mobile wallet payment.