Computer vision an application of AI, which is way beyond just seeing and understanding the content of digital images, is playing a significant role in enabling digital transformation across different industry verticals. It is one of the very versatile, fastest growing trends, based on deep learning models, which is bringing transformational change in our everyday lives.

Computer vision captures, processes, analyzes, and understands digital images and videos. It allows computer and other machines to see, and recognize like the human eye and generates actionable insights as per designed algorithms. It addresses unique business challenges and improves business performance through image processing and enhancement, Image classification, object detection, feature and pattern recognition, 3D image reconstruction and video analytics.

Let us check out some of the applications of computer vision in different industries.

Computer Vision in Automotive

Right from the assembly line and vehicle manufacturing process to vehicles on streets, computer vision is proving its acceptance and presence by making driving safer every day.

ADAS Applications: Applications of computer vision in ADAS are prominent. Computer vision through vision based ADAS (Camera based), RADAR, and LIDAR technologies are paving the way for automotive companies towards fully automated self-driving cars. Different systems inside a car perform different tasks like camera based ADAS provides visual representation, Radar works in case of low visibility, and LIDAR provides 3D representation of vehicle’s surroundings with object recognition. However, all these applications of ADAS are possible with computer vision technologies, which together provides a holistic solution in ADAS applications. This allows the driver to have better awareness of his surroundings while driving, and at the same time have more control.

• Automotive Gesture Recognition: Automotive gesture recognition with computer vision is the next level in road safety, which is based on deep learning and machine learning capabilities. Gesture recognition technology monitors the driver’s facial, hand gestures (Talking, texting, operating radio, having food and drinks while driving, etc.), and notifies if it differs from the pre-programmed recognizable gestures. Facial expressions like eye blinking, drowsiness and head movements are recognized with computer vision technologies and sends audible or visual alerts to notify the driver.

Computer vision is also very helpful in managing transportation and fleets when it comes to managing safety and security of passengers, drivers, and goods. Vision based solutions backed by automotive cameras (Dash cams, outward facing cameras) and telematics solutions play a key role in insurance telematics and manages fleet operations seamlessly.

Computer Vision in Retail

Improving Shopping Experience: Beyond ensuring security, spillage detection, and theft control, video analytics in retail with computer vision and artificial intelligence is more focused on improving the customer’s shopping experience and optimizing operations. Retail stores with computer vision and machine learning capabilities deployed at costumer touch points, not only gather customer’s data, but also process information about product placement, in-shelf product inventory, and customer need for the store employees to serve better.

Generating Valuable Insights: Computer vision in retail, with the help of in-store cameras, cameras in shelves, captures images of the products in the aisles and process them to draw actionable insights. This helps in digitizing every single detail of the products kept in aisles like assortments, shelf share, product availability, new products launched, brands and variants, pricing and discounts and out of stock products. In-store vision based technologies and deep learning algorithms help in generating product insights like if the products are placed in the proper place, impact of product placement on its sales, product promotion, creating brand awareness and more.

The latest trend in the retail industry is applying computer vision to provide end-to-end contactless solutions and reduce checkout time for their customers. Computer vision with deep learning algorithms are providing solutions to detect customers and their selected products for easy checkout with EPOS integration and object detection.

Computer Vision in Manufacturing

Production lines in hi-tech manufacturing units are highly complex and automated.Computer vision technologies in manufacturing units are very useful and they have unprecedented benefits to the business, like:

• Predictive Maintenance: Modern manufacturing units are equipped with very expensive automated production lines with conveyer units and robotics, and a company can never afford to have an unexpected breakdown of any part of the system. Even a mild breakdown in the production line, due to defect in the system, can be very disastrous for the business. This is where the role of computer vision comes into the picture, which analyzes every component of the production line and diagnose even the minute defects in the system. Based on the detailed and precise investigation, computer vision systems can predict any chances of future failure in the system, notifies technical team to fix that cause, and ensures no downtime in the production.
• Identifying Defects: Inspection for the defects in the industrial setup can be very risky, tedious, costly and time consuming, and sometimes it is next to impossible to detect any defects in the machines manually. Computer vision technologies in such cases help in eliminating risks for the workers and works precisely to identify cracks, corrosion, leaks and other anomalies in the machines. Industries like automotive, pharmacy, textile, energy, etc. are using computer vision technologies to run their processes free from defects.
• Product Quality Inspection: In conventional manufacturing units, quality inspection of the products is the last step in the production cycle, which compromises with the production capacity, time, labor and cost of the production setup. With the introduction of computer vision backed with AI and ML techniques, the quality of the products with their packaging are inspected at every stage of production with high precision and accuracy, resulting in minimal waste of the product, cost and efforts.

 Computer vision in Security and Surveillance

One of the early adopters of the computer vision technologies is security and surveillance industry. It is computer vision, which has exponentially improved the techniques and precision in video surveillance and intelligent video analytics. The volume of data generated by video surveillance systems depends on the number and types of video cameras and their resolution for specific projects. The huge amount of video feeds are of no use, unless some critical information can be generated. Computer vision has made this possible with use of AI and ML in video analytics.

Computer vision capabilities in security and surveillance are based on video management software and its hardware, third party devices (like sensors, alarms, access control devices), network, interfaces, signal processing capabilities, pattern and object recognition, etc.  Some of the key applications of computer vision in different industries are:

• Retail: In retail, it is computer vision algorithms which have helped in improving the security of the store with advanced video analytics like motion detection, face detection, people counting, queue management, heat mapping, gesture recognition, vandalism, and trespassing detection etc.

• Fleet Management: In Fleet management, computer vision is used to ensure safety and security of the vehicles in transit, consignment, driver and passengers, and helps in optimizing fleet routes. It improves fleet operations by monitoring driver behavior, incident capture, route optimization, consignment tracking, time management, number plate recognition, etc.

• City Surveillance: The conception of smart city is impossible without computer vision technologies. The security of the public places like parking lots, bus terminals, railway stations, subways, hospitals, highways, cross roads, traffic junctions etc. their monitoring with advanced video analytics is driven by computer vision algorithms. Some of the vision based applications in city surveillance is crowd detection, face recognition/capture, crowd detection, camera tampering, , vehicle tracking, number plate recognition, left/missing object detection, tailgating, illegal parking, speeding vehicles, vehicle wrong way detection etc.

Applications of computer vision can be applied in many other industries such as agriculture, oil and gas, life sciences, sports, consumer electronics and more. The reason behind adaptability of computer vision in almost every industry is its accuracy and precision, much more than a human vision. Computer vision algorithms, if designed properly for any of the use cases, can save time, improve productivity, and reduce operating costs significantly.

eInfochips has been instrumental is providing top notch computer vision based solutions, across industries. With over decades of experience in developing video analytics, machine learning, and vision based solutions, eInfochips continues to be a reliable solutions partner for various companies around the world. To know more about our computer vision, ML, and video analytics, watch our webinar.