The image recognition market is expected to grow from USD 46.7 billion in 2024 to USD 98.6 billion by 2029 at a Compound Annual Growth Rate (CAGR) of 16.1% during the forecast period. Continuous advancements in artificial intelligence (AI), deep learning, and computer vision technologies have significantly improved image recognition software's accuracy and capabilities, driving the market growth during the forecast period.
For instance, in the retail sector, companies like Zalando and ASOS utilize image recognition algorithms to offer personalized shopping experiences, enabling customers to search for products using images rather than keywords; this has enhanced user engagement and increased conversion rates and sales for these retailers. European hospitals and research institutions in healthcare also leverage image recognition technology for medical imaging analysis and diagnostics. For instance, the UK's National Health Service (NHS) has implemented image recognition systems to assist radiologists in interpreting medical images, leading to faster and more accurate diagnoses. In addition, government initiatives such as the European Commission's Digital Single Market Strategy and funding programs like Horizon Europe further support research and development in image recognition technology, driving innovation and competitiveness in the European market.
Note: The rest of the World consists of the Middle East & Africa, and Latin America
Note: Tier 1 companies have revenues of more than USD 100 million; tier 2 companies' revenue ranges from USD 10 million to USD 100 million; and tier 3 companies' revenue is less than 10 million
Source: Secondary Literature, Expert Interviews, and Analysis
Some of the significant vendors offering image recognition software and services across the globe include Google (US), Qualcomm (US), AWS (US), Microsoft (US), Toshiba (Japan), NVIDIA (US), Oracle (US), NEC (Japan), Huawei (China), Hitachi (Japan), Trax (Singapore), Samsung (South Korea), STMicroelectronics (Switzerland), ON Semiconductor Corporation (US), Snap2Insight (Portland), Attrasoft (US), Sterison (India), Unicsoft (UK), ParallelDots (US), Vue.ai (US), Catchoom (Spain), Wikitude (Austria), Ximilar (Czech Republic), Imagga Technologies (Bulgaria), Blippar (UK), Clarifai (US), LTU Technologies (France), and DeepSignals (US).
As per application area, the scanning & imaging segment is expected to grow at a higher CAGR during the forecast period.
Image recognition technology seamlessly integrates with existing workflow systems and document management platforms. Integrating with scanning devices, document repositories, and business applications enables end-to-end automation of document processing workflows, improving overall efficiency and productivity. Image recognition automates data extraction from scanned documents, such as invoices, forms, or receipts. It can identify and extract key data fields, such as names, dates, amounts, and reference numbers, with high accuracy. This streamlines data entry processes, reduces manual errors, and improves data quality. Image recognition technology can classify documents based on their visual content, such as layout, structure, or keywords; this allows workflow systems to automatically route documents to the correct workflows, departments, or users, speeding up processing times and improving organizational efficiency.As per organization size, large enterprises will hold a larger market share in 2024.
Image recognition automates manual tasks such as data entry, document sorting, and quality control. Analyzing images and identifying relevant information reduces the need for human intervention, saving time and labor costs. Mage recognition analyzes visual data to identify inefficiencies or bottlenecks in operational processes. Monitoring workflows and analyzing process steps' images helps organizations identify optimization opportunities and improve overall efficiency. In industries such as manufacturing and utilities, image recognition monitors equipment performance and detects potential issues. Analyzing images from sensors or cameras identifies abnormalities or signs of wear and tear, enabling proactive maintenance and minimizing downtime.As per region, Europe will witness the second-largest market share during the forecast period.
Europe has advanced technological infrastructure, including high-speed internet connectivity, robust computing resources, and a skilled workforce in artificial intelligence (AI) and computer vision. These technological capabilities enable the development and deployment of sophisticated image recognition solutions across various industries. European countries have made significant strides in advancing image recognition capabilities.For instance, in the retail sector, companies like Zalando and ASOS utilize image recognition algorithms to offer personalized shopping experiences, enabling customers to search for products using images rather than keywords; this has enhanced user engagement and increased conversion rates and sales for these retailers. European hospitals and research institutions in healthcare also leverage image recognition technology for medical imaging analysis and diagnostics. For instance, the UK's National Health Service (NHS) has implemented image recognition systems to assist radiologists in interpreting medical images, leading to faster and more accurate diagnoses. In addition, government initiatives such as the European Commission's Digital Single Market Strategy and funding programs like Horizon Europe further support research and development in image recognition technology, driving innovation and competitiveness in the European market.
The breakup of the profiles of the primary participants is below:
- By Company: Tier I: 33%, Tier II: 25%, and Tier III: 42%
- By Designation: C-Level Executives: 31%, Director Level: 34%, and Others: 35%
- By Region: North America: 42%, Europe: 28%, Asia Pacific: 22%, Rest of World: 8%
Note: The rest of the World consists of the Middle East & Africa, and Latin America
Note: Tier 1 companies have revenues of more than USD 100 million; tier 2 companies' revenue ranges from USD 10 million to USD 100 million; and tier 3 companies' revenue is less than 10 million
Source: Secondary Literature, Expert Interviews, and Analysis
Some of the significant vendors offering image recognition software and services across the globe include Google (US), Qualcomm (US), AWS (US), Microsoft (US), Toshiba (Japan), NVIDIA (US), Oracle (US), NEC (Japan), Huawei (China), Hitachi (Japan), Trax (Singapore), Samsung (South Korea), STMicroelectronics (Switzerland), ON Semiconductor Corporation (US), Snap2Insight (Portland), Attrasoft (US), Sterison (India), Unicsoft (UK), ParallelDots (US), Vue.ai (US), Catchoom (Spain), Wikitude (Austria), Ximilar (Czech Republic), Imagga Technologies (Bulgaria), Blippar (UK), Clarifai (US), LTU Technologies (France), and DeepSignals (US).
Research coverage:
The market study covers the image recognition market across segments. It aims to estimate the market size and the growth potential of this market across different market segments, such as offering, technology, application area, organization size, vertical, and region. It includes an in-depth competitive analysis of the key players in the market, their company profiles, key observations related to product and business offerings, recent developments, and key market strategies.Reasons to buy this report:
The report will help the market leaders/new entrants with information on the closest approximations of the revenue numbers for the overall image recognition market and the subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to position their businesses better and plan suitable go-to-market strategies. The report also helps stakeholders understand the market pulse and provides information on key market drivers, restraints, challenges, and opportunities.The report provides insights on the following pointers:
- Analysis of critical drivers (increasing demand for image recognition in the automotive industry, rising demand for security applications and products enabled with image recognition functions, increasing use of high bandwidth data services, and technological advancements to boost the demand for image recognition among CPG and retail components), restraints (high installation cost of Image recognition services and data privacy concerns and regulatory challenges), opportunities (integration of AI capabilities with image recognition solutions, increase in demand for big data analytics, and increase in demand in the healthcare industry), and challenges (training models to generalize well to natural world settings and limited dataset quality) influencing the growth of the image recognition market.
- Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the image recognition market.
- Market Development: Comprehensive information about lucrative markets - the report analyses the image recognition market across varied regions.
- Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the image recognition market.
- Competitive Assessment: In-depth assessment of market shares, growth strategies, and service offerings of leading players Google (US), Qualcomm (US), AWS (US), Microsoft (US), Toshiba (Japan), NVIDIA (US), Oracle (US), NEC (Japan), Huawei (China), Hitachi (Japan), among others in the image recognition market.
Table of Contents
1 Introduction
2 Research Methodology
3 Executive Summary
4 Premium Insights
5 Market Overview and Industry Trends
6 Image Recognition Market, by Offering
7 Image Recognition Market, by Technology
8 Image Recognition Market, by Organization Size
9 Image Recognition Market, by Application
10 Image Recognition Market, by Vertical
11 Image Recognition Market, by Region
12 Competitive Landscape
13 Company Profiles
14 Adjacent/Related Markets
15 Appendix
Companies Mentioned
- Qualcomm
- Aws
- Microsoft
- Toshiba
- Nvidia
- Oracle
- Nec Corporation
- Huawei
- Hitachi
- Trax
- Stmicroelectronics
- On Semiconductor Corporation
- Snap2Insight
- Attrasoft
- Sterison
- Unicsoft
- Paralleldots
- Vue.AI
- Catchoom
- Wikitude
- Ximilar
- Imagga Technologies
- Blippar
- Clarifai
- Ltu Technologies
- Deepsignals
Methodology
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Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 307 |
| Published | March 2024 |
| Forecast Period | 2024 - 2029 |
| Estimated Market Value ( USD | $ 46.7 Billion |
| Forecasted Market Value ( USD | $ 98.6 Billion |
| Compound Annual Growth Rate | 16.1% |
| Regions Covered | Global |
| No. of Companies Mentioned | 27 |
