Global Image Recognition Market Outlook 2020-2027: Lucrative Growth Opportunities When Combined With AI

DUBLIN, April 15, 2020 /PRNewswire/ -- The "Image Recognition Market Size, Share & Trends Analysis Report by Technique, by Application, by Component (Hardware, Software), by Deployment Mode, by Vertical, by Region, and Segment Forecasts, 2020-2027" report has been added to ResearchAndMarkets.com's offering.

The global image recognition market size is expected to reach USD 109.4 billion by 2027, expanding at a CAGR of 18.8% from 2020 to 2027.

Image processing and recognition have evolved with numerous powerful applications, such as security and surveillance, and medical imaging that have created a great value from a business perspective. Functions of figure identification, such as facial or object recognition, visual geolocation, barcode reading, and automated driver assistance, among other industrial automation-related functions, have demonstrated the versatility of this technology.

When combined with AI, this technology has begun to create valuable growth opportunities in several verticals, such as gaming, social networking, and e-commerce. For instance, Twitter and Facebook, two major platforms in the world of social networking, have benefited from the technology in terms of audience engagement as they have created a more connected experience by encouraging users to share images and tag their friends.

The advent of digital cameras, particularly cameras built into smartphones, has led to an exponential growth in the volume of digital content in the form of images and videos. A vast amount of visual and digital data is being captured and shared through several applications, websites, social networks, and other digital channels.

Several businesses have leveraged this online content to deliver better and smarter services to their customers, with the use of digital image processing. For instance, in October 2019, SnapPay Inc., a U.S. based payment platform provider, has launched facial recognition payment technology in the North America region. By using this thechnology in its payment solution, the company has aimed at allowing its customers a new level of convenience for payments at retail outlets.

However, data cleaning and hardware processing power remain as the two significant challenges involved in building areliable technology. Also, considering the time, complexity, and cost associated with software development for image identification, many companies may not have the resources who can produce acceptable and accurate results.

Therefore, several companies are taking strategic initiatives to expand their business with the help of image processing and recognizing techniques. For instance, in July 2019, Star Alliance, a global airline, announced a partnership with NEC Corporation to develop a biometric data-based identification platform for the pass-through areas at the airports, such as boarding gates and check-in kiosks. This AI-based platform and biometric passport would help the passengers to get through passport control without the need to show documents to the border officials.

Further key findings from the report suggest:

• Automated image organization offered by cloud-based applications and telecom companies is one of the most popular uses of the technology that has improved user experience and drawn the customers' attraction toward this technology
• Several benefits, such as better security and automation of identification, are the factors encouraging the implementation of facial recognition at major public spaces or events
• Advent of large-scale cloud-hosted AI and machine learning platforms offered by tech giants, has led to the development of image processing software with multiple functions such as facial and object recognition, and landmark detection
• Growing integration of digital image processing and mobile computing platforms in various applications such as digital shopping and document verification are propelling the image recognition market growth
• Key players in the market are Attrasoft, Google, Catchroom, Hitachi, Honeywell International, LTUTech, NEC Corporation, Qualcomm Technologies, Slyce Acquisition, and Wikitude, among others

Key Topics Covered

Chapter 1 Methodology and Scope
1.1 Information Procurement and Research Scope
1.2 Information Analysis
1.3 Market Formulation & Data Visualization
1.4 Market Scope and Assumptions
1.4.1 Secondary Sources
1.4.2 Primary Sources

Chapter 2 Executive Summary
2.1 Image Recognition - Industry Snapshot & Key Buying Criteria, 2016-2027
2.2 Image Recognition - Segment Trends
2.2.1 Technique
2.2.2 Application
2.2.3 Component
2.2.4 Deployment Mode
2.2.5 Vertical
2.2.6 Region

Chapter 3 Industry Outlook
3.1 Image Recognition - Market Definition
3.2 Market Segmentation & Scope
3.2.1 Technique
3.2.1.1 QR/Barcode Recognition
3.2.1.2 Object Recognition
3.2.1.3 Facial Recognition
3.2.1.4 Pattern Recognition
3.2.1.5 Optical Character Recognition
3.2.2 Application
3.2.2.1 Augmented Reality
3.2.2.2 Scanning & Imaging
3.2.2.3 Security & Surveillance
3.2.2.4 Marketing & Advertising
3.2.2.5 Image Search
3.2.3 Component
3.2.3.1 Hardware
3.2.3.2 Software
3.2.3.3 Service
3.2.4 Deployment Mode
3.2.4.1 On-Premise
3.2.4.2 Cloud
3.2.5 Vertical
3.2.6 Region
3.3 Image Recognition Market Size and Growth Prospects
3.4 Image Recognition - Process Flow Analysis
3.5 Market Dynamics
3.5.1 Market Driver Analysis
3.5.1.1 Extended Reach of Image Database and Open Source Frameworks
3.5.1.2 Growing Adoption of Image Recognition in Different Verticals
3.5.2 Market Restraint Analysis
3.5.2.1 High Costs Associated with Image Recognition Systems and Lack of High Resolution in Images
3.6 Key Opportunities - Prioritized
3.7 Industry Analysis - Porter's
3.8 Image Recognition Market - Company Analysis
3.8.1 Key Company Analysis, 2019
3.8.2 Vendor Landscape
3.9 Image Recognition Market - Start-Up Analysis
3.9.1 Blinkfire Analytics Inc.
3.9.2 Gumgum Inc.
3.9.3 Social Rewards
3.9.4 Kuznech
3.9.5 Kairos AR Inc.
3.9.6 Sparktrend
3.9.7 Cloudsight Inc.
3.9.8 Chooch Intelligence Technologies Co.
3.9.9 Pomika
3.9.10 Moodstocks
3.10 Image Recognition - PEST Analysis

Chapter 4 Image Recognition Market: Technique Estimates & Trend Analysis
4.1 Image recognition Market: Technique Movement Analysis
4.1.1 QR/Barcode Recognition
4.1.2 Object Recognition
4.1.3 Facial Recognition
4.1.4 Pattern Recognition
4.1.5 Optical Character Recognition

Chapter 5 Image Recognition Market: Application Estimates & Trend Analysis
5.1 Image Recognition Market: Application Movement Analysis
5.1.1 Augmented Reality
5.1.2 Scanning & Imaging
5.1.3 Security & Surveillance
5.1.4 Marketing & Advertising
5.1.5 Image Search

Chapter 6 Image Recognition Market: Component Estimates & Trend Analysis
6.1 Image Recognition Market: Component Movement Analysis
6.1.1 Hardware
6.1.2 Software
6.1.3 Service

Chapter 7 Image Recognition Market: Deployment Mode Estimates & Trend Analysis
7.1 Image Recognition Market: Deployment Mode Movement Analysis
7.1.1 On-Premise
7.1.2 Cloud

Chapter 8 Image Recognition Market: Vertical Estimates & Trend Analysis
8.1 Image Recognition Market: Vertical Movement Analysis
8.1.1 Retail & E-Commerce
8.1.2 Media & Entertainment
8.1.3 BFSI
8.1.4 Automobile & Transportation
8.1.5 Telecom & IT
8.1.6 Government
8.1.7 Healthcare
8.1.8 Others

Chapter 9 Image Recognition Market: Regional Estimates & Trend Analysis
9.1 Image Recognition Market: Regional Movement Analysis
9.2 North America
9.3 Europe
9.4 Asia-Pacific
9.5 South America
9.6 Middle East & Africa (MEA)

Chapter 10 Competitive Landscape
10.1 Company Profiles
10.1.1 Attrasoft Inc.
10.1.2 Catchoom
10.1.3 Google Inc.
10.1.4 Hitachi Ltd.
10.1.5 Honeywell International Inc.
10.1.6 LTUTech
10.1.7 NEC Corporation
10.1.8 Qualcomm Technologies Inc.
10.1.9 Slyce Acquisition Inc.
10.1.10 Wikitude GmbH

For more information about this report visit https://www.researchandmarkets.com/r/yi8x4q

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