Global Image Recognition in Retail Market 2020-2025: Market is Estimated to be $1.5 Bn in 2020 and is Expected to Reach $3.7 Bn by 2025, Growing at a CAGR of 20%


Dublin, Jan. 25, 2021 (GLOBE NEWSWIRE) -- The "Global Image Recognition in Retail Market (2020-2025), by Technology, Component, Application, Deployment, Geography and the Impact of Covid-19 with Ansoff Analysis" report has been added to's offering.

The Global Image Recognition in Retail Market is estimated to be USD 1.5 Bn in 2020 and is expected to reach USD 3.7 Bn by 2025, growing at a CAGR of 20%.

Image Recognition means identifying a specific image and placing it in a predetermined category. It uses computer algorithms for digital image processing and thus helps in processing videos and removing blur images. The technology further allows images to convert into two or more defined dimensions, which categorize the digital image processing as multidimensional systems.

Image recognition in retail includes the technologies which help to enhance the in-store experiences of customers. The use of high bandwidth data services in the retail and BFSI sector can be attributed to the growth of the image recognition market. android devices with cameras are attracting vendors to invest in the market. Increasing demand for security in products and applications is also influencing the growth of the image recognition market.

Large enterprises in different sectors, such as retail, automotive, healthcare, and defense, are increasingly adopting image recognition technology. Several other fields, such as self-driving vehicles, automated image organization of visual websites, and face identification on social networking websites, are using the Image recognition technology powered by machine learning.

Government agencies such as law enforcement agencies are also using facial recognition technology for their safety and security purposes. Airports are also using face remembrance technology at security checkpoints for security purposes. Recent advancements in artificial intelligence and machine learning have highly contributed to the growth of Image Recognition and Object Detection in retail.

Certain factors may create hindrances in the growth of image recognition in the retail market, such as the high cost involved in making the image recognition systems, lack of technical skills, etc. Thus, companies who lack resources are unable to adopt this technology even if they are interested in image recognition.

On the other hand, a huge number of social media applications are available on the internet, and a good amount of the population is daily uploading a billion images per day on social media platforms such as Facebook, WhatsApp, Snapchat, Instagram, etc. which helps in increasing the adoption of image recognition and will drive the growth of the Global Image Recognition in Retail Market.

Market Dynamics


  • Need to Increase On-Shelf Availability, Enhance Customer Experience, and Maximize ROI
  • Increasing the Use of Image Recognition Applications
  • Increasing Use of High Bandwidth Data Services
  • Increasing Demand for Security Applications and Products Enabled with Image Recognition Functions


  • High Risk Related to Customer Data Thefts
  • High Cost of Installation of Image Recognition Systems


  • Growing Adoption of Cloud-Based Image Recognition Solutions
  • Rising Demand for Brand Recognition Among End Users
  • Increasing Demand for Big Data Analytics

Key Topics Covered:

1. Report Description
1.1 Study Objectives
1.2 Market Definition
1.3 Currency
1.4 Years Considered
1.5 Language
1.6 Key Shareholders

2. Research Methodology
2.1 Research Process
2.2 Data Collection and Validation
2.2.1 Secondary Research
2.2.2 Primary Research
2.3 Market Size Estimation
2.4 Assumptions of the Study
2.5 Limitations of the Study

3. Executive Summary

4. Market Overview
4.1 Introduction
4.2 Market Dynamics
4.2.1 Drivers
4.2.2 Restraints
4.2.3 Opportunities
4.2.4 Challenges
4.3 Trends

5. Market Analysis
5.1 Porter's Five Forces Analysis
5.2 Impact of COVID-19
5.3 Ansoff Matrix Analysis
5.4 SWOT Analysis

6. Global Image Recognition in Retail Market, By Technology
6.1 Introduction
6.2 Barcode Recognition
6.3 Digital Image Processing
6.4 Object Recognition
6.5 Facial Recognition
6.6 Other Technologies

7. Global Image Recognition in Retail Market, By Component
7.1 Introduction
7.2 Services
7.3 Software
7.4 Hardware

8. Global Image Recognition in Retail Market, By Application
8.1 Introduction
8.2 Visual Product Search
8.3 Marketing and Advertising
8.4 Security and Surveillance
8.5 Vision Analytics
8.6 Other Applications

9. Global Image Recognition in Retail Market, By Deployment
9.1 Introduction
9.2 Cloud
9.3 On-Premises

10. Global Image Recognition in Retail Market, By Geography
10.1 Introduction
10.2 North America
10.2.1 US
10.2.2 Canada
10.2.3 Mexico
10.3 South America
10.3.1 Brazil
10.3.2 Argentina
10.4 Europe
10.4.1 UK
10.4.2 France
10.4.3 Germany
10.4.4 Italy
10.4.5 Rest of Europe
10.5 Asia-Pacific
10.5.1 China
10.5.2 Japan
10.5.3 India
10.5.4 Australia
10.5.5 Rest of APAC
10.6 Middle East and Africa

11. Competitive Landscape
11.1 Competitive Quadrant
11.2 Market Share Analysis
11.3 Competitive Scenario
11.3.1 Mergers & Acquisitions
11.3.2 Agreements, Collaborations, & Partnerships
11.3.3 New Product Launches & Enhancements
11.3.4 Investments & Fundings

12. Company Profiles
12.1 Amazon
12.2 Google LLC
12.3 IBM Corporation
12.4 Microsoft Corporation
12.5 TRAX Retail
12.6 Qualcomm Technologies, Inc.
12.7 NEC Corporation
12.8 LTU Technologies
12.9 Catchoom Technologies S.L.
12.10 Honeywell International Inc.
12.11 Hitachi, Ltd.
12.12 Slyce Inc.
12.13 Wikitude GmbH
12.14 Attrasoft, Inc.
12.15 Planorama
12.16 Ricoh Innovations Corporation
12.17 Pattern Recognition Company GMBH
12.18 Intelligent Retail
12.19 Snap2Insight Inc.
12.20 Blippar

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