Dublin, July 28, 2020 (GLOBE NEWSWIRE) -- The "Image Recognition in Retail Market by Technology (Code Recognition, Digital Image Processing) Component (Software and Services), Application (Visual Product Search, Security Surveillance), Deployment Type, and Region - Global Forecast to 2025" report has been added to ResearchAndMarkets.com's offering.
Need to increase on-shelf availability, enhance customer experience, and maximize RoI expected to drive the growth of the image recognition in the retail market
The image recognition in the retail industry is driven by various factors, such as rising technological developments increases the adoption of image recognition solutions among retailers and growing need to increase on-shelf availability, enhance customer experience, and maximize RoI. However, high risk related to customer data thefts can hinder the growth of the market.
The recent COVID-19 pandemic is expected to impact the global retail industry. The prime impact of COVID-19 observed on the image recognition in the retail market is a reduction in in-store shoppers, resulting in a reduction in retail sales. Image recognition in retail includes technologies to improve the in-store experiences of customers. Since the disease is spreading enormously, shoppers are avoiding crowded places and are not gathering at public places such as malls and stores. This has adversely affected the sales rate of the retail sector due to the shutting down of stores and malls in the pandemic period resulting in hefty losses to owners.
Services segment to grow at a higher CAGR during the forecast period
Services form an integral part of the image recognition in retail software lifecycle; they include implementation, deployment, product upgrades, maintenance, and consulting. The services segment has been classified into professional and managed services. With the increasing adoption of the image recognition in retail software solutions, the need for these services is expected to increase, as they help companies reduce costs, increase the overall revenue, and enhance the overall performance of employees and organizations alike. Services help companies build successful customer relationships by continuously supporting them throughout their business tenure. Image recognition in retail vendors sometimes provides services via channel partners that can help strengthen the geographical reach of solution vendors and the cost-effectiveness of their software. Moreover, the growing demand for rich media is expected to drive companies, such as NEC Corporation, LTU, and Catchoom to offer integrated training services, professional services, and support and maintenance services.
Software segment to account for a higher market share during the forecast period
API combines technologies, automates several processes, and categorizes them to search through a large image collection or databases. API servers analyze images from the existing database and retrieve image features, such as image type, class, and colors, and image metadata, such as tags. It further allows users to store information and images in the database to maintain and organize their collections more effectively. The key task of the image processing software is to extract data from the available database and produce the required output. Advanced algorithms have also been developed to accurately identify objects in images and videos without the need for human calibration. Analytical solutions extract intelligent real-time videos via surveillance cameras.
The Asia Pacific to grow at the highest rate during the forecast period
Image recognition in the retail market in the Asia Pacific (APAC) is expected to grow at the highest CAGR during the forecast period. In the APAC region, there is a tremendous demand for image recognition in retail software and services. China, India, Japan, Australia and New Zealand (ANZ), and Singapore have emerged as undisputed leaders in the image recognition in the retail industry.
Key Topics Covered:
1 Introduction
1.1 Introduction to COVID-19
1.2 COVID-19 Health Assessment
1.3 COVID-19 Economic Assessment
1.3.1 COVID-19 Economic Impact - Scenario Assessment
1.4 Objectives of the Study
1.5 Market Definition
1.5.1 Inclusions and Exclusions
1.6 Market Scope
1.6.1 Market Segmentation
1.6.2 Years Considered for the Study
1.7 Currency Considered
1.8 Stakeholders
2 Research Methodology
2.1 Research Data
2.1.1 Secondary Data
2.1.2 Primary Data
2.1.2.1 Breakup of Primary Profiles
2.1.2.2 Key Industry Insights
2.2 Market Breakup and Data Triangulation
2.3 Market Size Estimation
2.3.1 Top-Down Approach
2.3.2 Bottom-Up Approach
2.4 Market Forecast
2.5 Assumptions for the Study
2.6 Limitations of the Study
3 Executive Summary
4 Premium Insights
4.1 Attractive Opportunities in the Image Recognition in Retail Market
4.2 North America: Market, by Component and Country, 2020
4.3 Market, by Deployment Type, 2020-2025
4.4 Market, by Component, 2020-2025
5 Market Overview
5.1 Introduction
5.2 Market Dynamics
5.2.1 Drivers
5.2.2 Restraints
5.2.3 Opportunities
5.2.4 Challenges
5.3 Adjacent Markets
5.4 Use Cases
5.4.1 Use Case 1: Paralleldots
5.4.2 Use Case 2: Trax
5.4.3 Use Case 3: Vispera
6 Image Recognition in Retail Market, by Technology
6.1 Introduction
6.1.1 Technology: COVID-19 Impact
6.2 Code Recognition
6.3 Digital Image Processing
6.4 Facial Recognition
6.5 Object Recognition
6.6 Other Technologies
7 Image Recognition in Retail Market, by Component
7.1 Introduction
7.1.1 Component: COVID-19 Impact
7.2 Software
7.3 Services
7.3.1 Professional Services
7.3.2 Managed Services
8 Image Recognition in Retail Market, by Application
8.1 Introduction
8.1.1 Application: COVID-19 Impact
8.2 Visual Product Search
8.3 Security and Surveillance
8.4 Vision Analytics
8.5 Marketing and Advertising
8.6 Other Applications
9 Image Recognition in Retail Market, by Deployment Type
9.1 Introduction
9.1.1 Deployment Type: COVID-19 Impact
9.2 On-Premises
9.3 Cloud
10 Image Recognition in Retail Market, by Region
10.1 Introduction
10.2 North America
10.3 Europe
10.4 Asia Pacific
10.5 Middle East and Africa
10.6 Latin America
11 Competitive Landscape
11.1 Introduction
11.1.1 New Solution Launches/Solution Enhancements
11.1.2 Partnerships and Collaborations
11.1.3 Mergers and Acquisitions
11.2 Competitive Leadership Mapping
11.2.1 Visionary Leaders
11.2.2 Innovators
11.2.3 Dynamic Differentiators
11.2.4 Emerging Companies
12 Company Profiles
12.1 Introduction
12.2 AWS
12.3 IBM
12.4 Google
12.5 Microsoft
12.6 Trax
12.7 Nec Corporation
12.8 Qualcomm
12.9 Catchoom
12.10 Slyce
12.11 Ltu
12.12 Intelligence Retail
12.13 Snap2Insight
12.14 Imagga
12.15 Paralleldots
12.16 Vispera
12.17 Blippar
12.18 Ricoh Innovations
12.19 Clarifai
12.20 Deepomatic
12.21 Shelfwise
12.22 Trigo
12.23 Wikitude
12.24 Huawei
12.25 Honeywell
12.26 Standard Cognition
12.27 Zippin
12.28 Right to Win
For more information about this report visit https://www.researchandmarkets.com/r/10qdzq
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