Market Overview

• The AI image recognition market was valued at USD 1.41 billion in 2018 and is projected to reach a market value of USD 5.32 billion by 2024 at a CAGR of 24.7% over the forecast period (2019 - 2024). Image recognition technologies comprise voice, iris, palm, hand vein pattern, fingerprints, retina, hand geometry, facial pattern recognition, object identification etc. Image recognition based on these indications can be applied across various fields, such as vehicular safety, advertising, security and surveillance, biometric scanning machines, pedestrian recognition, and E-commerce.
• The adoption of artificial intelligence (AI) technology is rising, owing to its ability to enhance and automate operations and enrich the user experience. Governments are also focusing on increasing their AI capabilities to revolutionize various sectors, from healthcare to transport. EU has committed to invest EUR 1.5 billion in AI to catch up with the United States and Asia.
• From the technical side, skills are needed to implement and develop road map infrastructure, manage security, and capture and analyze data.
• According to Eirik Thorsnes at UNI Research in Bergen, Norway, “There has been a tremendous development in recent years, and we are now surpassing the human level in terms of image recognition and analysis. Computers never get tired of looking at near-identical images and may be capable of noticing even the tiniest nuances that we humans cannot see. In addition, as it gets easier to analyze large volumes of images and video, many processes in society can be improved and optimized,"

Scope of the Report

Image recognition, in the context of machine vision, is the ability of software to identify objects, places, people, writing and actions in images. Computers can use machine vision technologies in combination with a camera and artificial intelligence software to achieve image recognition. Image recognition is used to perform a large number of machine-based visual tasks, such as labeling the content of images with meta tags, performing image content search, guiding autonomous robots and self-driving cars, and in accident avoidance systems.

Report scope can be customized per your requirements. Click here.

Key Market Trends

Banking Sector Expected to Witness Prominent Growth

• Images are real and omnipresent, and unlike other forms of data, they cannot be forged easily. These traits make images repositories of big data, and hence, exploiting such data can be a great source of information for financial institutions.
• The banking industry has been a major benefactor of AI, with firms in the BFSI industry relying on the technology for a diverse range of applications, like personalizing communication with customers, staying competitive in a continuously evolving market, and improving the productivity drastically through the automation of redundant tasks (which is a major task due to the conventional infrastructure in a number of old school financial institutions).
• Banks have tons of unstructured data on interactions with customers, customer photographs, and old documents, to name a few. The data, if deciphered well, can provide valuable inputs for the future of the financial institutions.
• Facebook can now identify and map 98% of its images correctly to the right person. Imaging technology is being used for identifying and removing fake social accounts. Such image-based fake identification has immense potential in enriching credit-scoring and risk-modeling of banks. Images could also be used by underwriters in risk assessment and fraud identification.

To understand key trends, Download Sample Report