Image Recognition in Retail Market Outlook (2023 to 2033)

According to Future Market Insights, image recognition in retail is expected to reach a market valuation of US$ 2.11 billion by the end of 2023, accelerating at a CAGR of 23% over the forecast period (2023 to 2033). Increasing numbers of retail outlets and online stores have led to rapid growth in the retail image recognition market. Machine learning and artificial intelligence advancements have been a major influence on the growth of image recognition in retail.

The growth of the market is supported by:

  • An increased automated tasks in inventory management, shelf stocking, and checkout process
  • Advancement in Technologies
  • Research and development are growing and investments are increasing
  • Increasing AI experiences, and personalized customer experience
  • Growing demand for smart mobile devices and implementation of image recognition technology
  • Enhanced security and prevent theft
  • Increased expansions of retail industries in rural and urban areas
  • Continues advancement in internet
  • Growing adoption of cloud-based image recognition solutions
  • Increased demand for Big Data Analytics

Stanford researchers found that manual audits in retail could have been more time-consuming and accurate. Data can be collected consistently and precisely using image recognition technology. Numerous studies have shown that customers prefer self-checkout options for their convenience, speed, and enjoyment.

With image recognition technology, the retail industry is already revolutionized, and its future potential is limitless. By analyzing past purchases and browsing histories, image recognition technology can provide personalized recommendations based on a customer's shopping behavior and preferences and expand the market

Tracking and managing inventory more efficiently is made possible using image recognition technology that automatically identifies and categorizes products on store shelves. Retailers are using this information to determine stock levels, the top-selling brands, and restocking needs.

Enhanced customer engagement: Image recognition technology can be used to create more engaging and interactive customer experiences, such as augmented reality shopping and virtual try-on.

Retailers utilize image recognition technology to detect fraudulent activities, including counterfeit products and returned merchandise. The use of image recognition can also be beneficial to retailers in terms of reducing costs since it automates tasks like inventory management and product classification that were previously done manually.

Analysis of large amounts of data can be achieved using photo recognition technology. Consumer behavior predictions can also be made by using technology. It is anticipated that image recognition technology will improve efficiency, reduce costs, and enhance customer experiences in the retail industry. Continuing advancements in this technology will lead to even more innovation and applications in the future.

Retailers in North America and Asia Pacific (APAC) are increasingly integrating image recognition technology into their businesses. Due to their unique market characteristics, image recognition technology adoption and implementation may vary in these regions.

A growing e-commerce sector, evolving consumer demands, and the increasing use of smartphones have made Asia Pacific one of the fastest-growing markets for image recognition in retail. Several retail chains in the region are establishing virtual try-on and augmented reality shopping experiences with their customers, using image recognition technology. Moreover, due to the high rate of mobile adoption in the region, image recognition technology is playing a major role in the development of mobile shopping apps that use image recognition technology. For example, Alibaba uses image recognition technology on its Taobao and Tmall platforms in China to improve the shopping experience.

The retail industry in North America has already adopted image recognition technology to a large extent. Image recognition technology helps retailers like Walmart and Amazon manage inventory more efficiently, reduce costs, and personalize shopping experiences. Security in retail stores can also be improved with image recognition technologies.

Although image recognition technology in retail has gained traction in the Asia Pacific region as well as North America, different market characteristics and consumer behaviors may influence its implementation and adoption. Although both regions offer significant opportunities and future possibilities in the retail sector with image recognition technology.

Data Points Key Statistics
Estimated Base Year Value (2022) US$ 1.9 billion
Expected Market Value (2023) US$ 2.11 billion
Anticipated Forecast Value (2033) US$ 16.8 billion
Projected Growth Rate (2023 to 2033) 23% CAGR

The image recognition technology can be utilized for retail applications to process, analyze and understanding images. Many retailers are implementing AI and image recognition technology in retail to deliver the next level of customer experience.

This is one of the major factors driving the growth for image recognition in retail market. Image recognition technology is also used for product recommendations, product discovery, & trend analysis in retail sectors.

Image recognition in retail offers number of applications across security, marketing, payment, shopping & customer service. Retailers are using image recognition solutions, to help improve in-store customer service, as well as possibly address showrooming, by allowing shoppers to scan a product with an app and pull up current inventory. Image recognition can help merchants retain sales from shoppers who compare prices online via their smartphones.

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Image Recognition in Retail Market: Drivers and Challenges


Increasing use of image recognition applications such as scanning & imaging, security & surveillance, marketing & advertising, are fueling the growth of the image recognition in retail market. The growing need for improving the accuracy of the biometric authentication process, drives the image recognition in retail market growth.

Furthermore, the rising demand for big data analytics and the need for product brand recognition in retail sectors, are major factors expected to fuel the new growth opportunities in the market. Image recognition in retail offers different benefits such as auditing product placement, detecting trends in product placement, assessing compliance and competition, and category analysis.

The reliability of such benefits drives the Image recognition in retail market growth.


However, the image recognition in retail market is also impacted significantly when the scanning process is not perfect due to poor lighting, blur, motion, or even physical problems.

Also, high cost of installation of image recognition systems, as well as technical issues regarding the compatibility with existing systems, are some of the factors challenging the growth of image recognition in retail market.

Image Recognition in Retail Market: Competition Landscape

Some of the prominent players providing image recognition solutions in retail are

  • Qualcomm Technologies, Inc.
  • NEC Corporation
  • Catchoom Technologies S.L.
  • Hitachi, Ltd.
  • Wikitude GmbH
  • Attrasoft, Inc.
  • Trax Retail
  • Snap2Insight Inc.
Sudip Saha
Sudip Saha

Principal Consultant

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Image Recognition in Retail Market: Regional overview

By geography, the image recognition in retail market has been segmented into North America, Europe, Latin America, East Asia, South Asia & Pacific, and Middle East & Africa. The market is currently dominated by Europe followed by North America, due to the advancements in image recognition technologies by the prominent vendors in these regions.

Moreover, Asia Pacific holds a comparatively higher market CAGR in the global image recognition in retail market, due to the growing advancements in the field of digital shopping and e-commerce, in this region.

The image recognition in retail market report is a compilation of first-hand information, qualitative and quantitative assessment by industry analysts, and inputs from industry experts and industry participants across the value chain.

The report provides in-depth analysis of parent market trends, macro-economic indicators, and governing factors, along with market attractiveness as per segment. The image recognition in retail market report also maps the qualitative impact of various market factors on market segments and geographies.

The report covers exhaustive analysis on

  • Image Recognition in Retail Market Segments
  • Image Recognition in Retail Market Dynamics
  • Image Recognition in Retail Market Size
  • Supply & Demand
  • Current Trends/Issues/Challenges
  • Competition & Companies Involved in the Market
  • Technology Landscape
  • Value Chain of the Market
  • Image Recognition in Retail Market Drivers and Restraints

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Regional analysis includes

  • North America (USA, Canada)
  • Latin America (Mexico, Brazil, Rest of Latin America)
  • Europe (Germany, Italy, United Kingdom, Spain, France, BENELUX, Russia, Rest of Europe)
  • East Asia (China, South Korea, & Japan)
  • South Asia & Pacific (India, ASEAN, Australia & New Zealand, Rest of South Asia & Pacific)
  • Middle East and Africa (GCC Countries, Turkey, South Africa, Rest of MEA)

Image Recognition in Retail Market: Segmentation

The image recognition in retail market has been segmented on the basis of component, technology, application, and region.


  • Hardware
  • Software
  • Services

basis of technology:

  • Digital Image Processing
  • Code Recognition
  • Optical Character Recognition
  • Object Recognition
  • Pattern Recognition

basis of application:

  • Scanning & Imaging
  • Image Search
  • Security & Surveillance
  • Augmented Reality
  • Marketing & Advertising
  • Others



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