ARTIFICIAL INTELLIGENCE IN COMPUTER VISION

Computer vision technology enables the computer system to understand the visual world and simulating human vision using the computational technique. This technology works the same as human vision. You will be amazed to know that computer vision trains machines to do the task in much less time with data, cameras, and algorithms. Artificial intelligence in computer vision is continuing to grow in industries such as energy, automotive, utilities, and manufacturing. Computer vision enables artificial intelligence-powered machines to analyze thousands in minutes and allows the production plants to automate the defects. It requires a larger database because these solutions analyze data repeatedly until they gain the required results. 

Computing power, hardware related to computer vision analysis, advanced mobile technology, and several neural networking algorithms have opened a new horizon for computer vision in AI. Computer vision emulates human vision using a digital image and understands the visual world. Digital images from videos, cameras, machines and deep learning models can precisely classify and recognize objects. According to the latest survey the computer vision market is expected to reach $48.6 billion by 2022. This field has gained incredible advancement with the increased accuracy rates of classification and object recognition. Computer vision is a computer science that combines technology and theory to build artificial systems for getting data from images or multi-dimensional data. According to research, the global artificial software market is expected revenue of 126 billion by 2025. 

How does computer vision technology work?

Computer vision is used for pattern recognition techniques to understand visual data. This technology works to find patterns, visualize data, and label objects. The wide availability of data helps deep learning experts to use this data to make the process more smart and accurate. 

Computer vision technology follows these steps to deliver the results.

1. Image acquisition:
2. Processing the imaging technology:
3. Understanding the imaging technique:

• Image acquisition: this technique is performed to translate the analog images into digital images, i.e. in the combination of zeros and ones. Different tools like digital cameras, webcams, embedded cameras, and laser range finders are used to prepare datasets. Even a large set can be acquired in real-time through, video, images, or 3D techniques for analysis. 
• Processing the imaging technology: this technique includes using modern applied mathematics algorithms to extract geometric elements, such as feature detection and matching, segmentation, classification, and edge detection. 
• Understanding the imaging technique: this step uses is the interpretive step that uses advanced level algorithms to conduct a deep analysis of the data for recognition, object tracking, and 3D scene mapping. In this final step, high-level algorithms are applied to the processed data to perform real analysis. This technique helps in decision-making.

Application of computer vision technology:

Today, Computer vision technology is to endeavors in everyday life, transportation, education, healthcare, and business. Below is the list of the most popular applications of computer vision technology. 

1. Role of computer visions in agriculture: today, many agricultural organizations are leveraging computer vision to monitor the harvest and enhance agricultural productivity. Artificial intelligence in computer vision helps to process images from planes, drones, or satellites to detect common agricultural problems such as plant health and weather analysis. Computer vision has several applications in this field, including yield tracking, drone-based crop monitoring, smart crop sorting and classification, and automatic spraying of pesticides. These applications help to crop, color, scan, texture, and shape. Computer vision technology is useful for weeding, forestry data, field security, and forestry data. 
2. Self-driving vehicles: Smart vehicles use multi-camera setups to make sense of their surroundings. The car has advanced features and 380-degree cameras to capture videos to detect objects such as objects near the vehicle, road marking, traffic lights, etc. another amazing feature of this smart car is to engage in advanced processes like behavior arbitration, path planning, and driving scene. The use of this technology in Tesla cars is autopilot. 

3. Uses of Facial recognition in computer vision: Facial recognition is used in smartphone applications, facial detection solutions, and the public security industry. Face recognition applications detect and recognize faces in public. Computer vision applications use recognition algorithms to capture images of large-scale faces in public. Facial recognition helps to prevent and detect criminal activities. This application is useful to match the image of people’s faces. Facial recognition technology works very fast and a front face camera is used for mobile devices to process the image and tell whether the user who is holding a mobile is authorized on the mobile device. 

4. This use of computer vision in human posture estimation: Another wonderful application of computer vision is human pose estimation which can analyze and detect human posture. Human posture estimation is specifically used in physical therapy, gaming, robotics, and fitness coaching. This fitness app helps to capture human movements while exercising, recognize the user’s mistakes, and determine body posture. The gaming device can easily monitor player actions through computer vision technology. This technology can recognize human movements and detect the position of their skeletal joints. 

5. Computer vision used in smart cities app: It is the most interesting and incredible application of computer vision. This app use cameras, low-power sensors, and artificial intelligence algorithms to monitor the efficiency of smart cities. This technology allows city administrators to manage assets. This technology works magically in smart cities for crowd analysis, traffic analysis, weapon detection, infrastructure inspection, and vehicle counting. 

6. Use of computer vision in insurance: this technology leverages artificial intelligence vision for automated assessment, visual inspection, forward-looking analytics, and risk management. Artificial intelligence in computer vision enables computers to understand objects and events precisely. Computer vision works for fraud detection, roof underwriting, NLP for insurance, wildfire risk assessment, key takeaways, and vehicle damage assessment. This technology helps to reduce the risk of fraud. There are several types of insurance that include asset insurance, health, house, fire, and vehicle. 

7. Use of computer vision in logistics: artificial intelligence in this application apply deep learning to save costs by reducing human errors, accelerating operations, and predictive maintenance. 

8. Use of computer vision in healthcare: Healthcare systems rely on image classification and pattern detection for diagnostic purposes. Computer vision technology helps healthcare professionals to diagnose conditions. This technology is used for medical imagery and this technique is prevalent in ophthalmology, pathology, and radiology. Computer vision is used in MRI and X-ray scans. The Microsoft InnerEye helps to deliver accurate diagnoses. 

9. Computer vision technology used in manufacturing: Computer vision is the most popular technology in manufacturing plants and is used in AI-powered inspection systems. These systems are used in warehouses and R&D laboratories. Computer vision is used in inspection systems that scan the environment and notifies if a low-quality product and breakdown are detected. Computer vision technology is used in manufacturing for process automation, automated product inspection, increase workforce, and object counting. Employees can also use this technology in quality monitoring activities and packaging. 

10.  Computer vision technology used in Retail systems: Its main example is video surveillance cameras in retail stores that can track the customers counting, waiting times, people’s movement patterns, and consumer attention. With the help of this technology retail stores can also analyze and personalize advertisements, making loss prevention and people’s mood. 

11. The use of computer vision technology in pharmaceutical: this intelligent technology in the pharmaceutical field is used for visual inspection for equipment cleaning, packaging and blister detection, and capsule recognition. 

12. Use of computer vision in the field of Education: Computer vision technology is used for applications such as attendance monitoring, knowledge acquisition, school logistic support, and regular assessments. Teachers use this technology to evaluate the learning process, tweak the teaching process, and identify disengaged students. Webcams help to monitor students during an exam and analyze body behavior and eye movements. 

13.  Use of computer vision in transportation: The use of Artificial intelligence in computer vision in Transportation: computer vision technology is being used to increase transportation efficiency and detect traffic signal violators. Computer vision technology is used to detect speeding, wrong-side driving violations, and transportation systems for traffic flow analysis. 

Computer vision research:

Here is the few computer vision research that involves the basics of visual perception tasks. 

1. Computer vision is used for image classification: It is an amazing technology that can see and classify images such as a person’s face, football, a cat, etc. image classification technology can identify that a given image belongs to a certain group. For instance, social media use this technique to automatically predict and separate objectionable images uploaded by people. 

2. Computer vision technology is used for object detection: this technique use image classification to recognize a certain group of image and then tabulate and detect their appearance in video or image. Object detection can analyze image data and identify machinery that requires maintenance.

3. Object recognition used by computer vision technology: this technique can easily determine whether image data contains object classes or one or multiple specified. This smart technology can count the stock in your inventory store or people in an event. The application can help you to spot dangerous weapons like guns and knives. 

4. Object tracking used by computer vision: this wonderful application tracks and follows an object after detection. This task is performed during image capturing in sequence or real-time video feeds. 

5. The computer vision technique uses a text detection method: an image recognition system helps to identify text from images. This technique can help in transforming digital form, historic books, and papers. Industries are getting benefits from using this text recognition application. 

6. Visual search technique used by computer vision: this technology helps you to separate several images and find the optimum visually relevant product in a specified time frame. This application enables businesses to enhance their shopping experience and deliver precise outcomes to their online users. Ecommerce leaders and retailers are using visual search to attract and retain customers.

7. Google translate used by computer vision: Google Translate is open on internet-enabled devices with cameras. This app detects the text and automatically translates it into the user’s language. Google uses this technology in lens service. These services can instantly translate over 100 languages. Google translator is benefiting the people across Europe, Asia, and Africa with numerous languages. More than half of Google’s translation toolkit languages require no network connection and are available for offline use.

8.  Computer vision uses Facebook 3D Photo: This wonderful technology required a smartphone with dual cameras to create a depth map and generate 3D images. user can turn his ordinary two-dimensional image into a 3D photo. Users can easily scroll, rotate or tilt on their smartphones to view these 3D photographs from different perspectives. Thanks to this technology users can apply realistic-looking 3D images to the photo. 

9. Faceapp technology used by computer vision: Faceapp allows the systems to learn every small detail of the appearance of the human face. It is a most popular image application that can modify visual inputs of human faces to change age, gender, and other features. Faceapp technology can recognize a face with deep learning to identify key facial features such as jawline, eyelids, nose bridge, and cheekbones. This app can also enable to modification of hairlines, simulate wrinkles and make realistic changes to photographs of a human face.

Final thoughts:

Computer vision enables a machine to understand the visual world. The computer system can accurately locate and recognize videos and images to obtain meaningful data from the real world. This brilliant technology enables a bar code scanner to detect the stripes in a universal product code. This innovative technology is used across the business and enhances the user experience with increased security and reduction of cost. Artificial intelligence’s market is growing as fast and is estimated to reach $26.2 billion by 2025. Artificial intelligence in computer vision is expected to help us lead safer, happier lives and stay healthier.