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1347990

全球光學字符識別市場 - 2023-2030

Global Optical Character Recognition Market - 2023-2030

出版日期: 2023年09月11日 | 出版商:

DataM Intelligence | 英文 185 Pages | 商品交期: 最快1-2個工作天內

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簡介目錄

概述

2022年全球光學字符識別市場規模達到122億美元，預計到2030年將達到316億美元，2023-2030年預測期間年複合成長率為15.2%。

各行業採用數位化轉型的持續變化導致需要數位化和處理的紙質文檔數量大幅增加。 OCR 通過自動化提取過程顯著提高了數據的效率和生產力，並且消除了手動數據輸入的需要，從而減少了錯誤並節省了時間。

許多企業正在採用 OCR 來自動化各種流程，例如發票處理、契約管理和各種形式的數據提取，這種自動化可以加快決策過程並提高效率。醫療保健行業更廣泛地採用 OCR，因為它將患者記錄、病歷和處方轉換為數位格式。

北美是全球光學字符識別市場的成長地區之一，佔據超過1/3的市場佔有率，是技術創新的中心。組織正在採用 OCR，將紙質文檔轉換為數位格式。基本上，OCR 用於研究機構，它增強了可訪問性並支持線上學習平台。

動力學

為視障人士採用 OCR

光學字符識別涉及人工智慧、機器學習和電腦視覺方面的重大進步，這些進步具有更準確、更可靠的 OCR 功能，使得將印刷文本準確轉換為輔助設備可以讀取的數位格式成為可能。 OCR與人工智慧、機器學習技術的融合，能夠不斷提升識別準確率。

機器學習算法可以適應不同的字體、樣式和語言，增強OCR有效識別和轉換文本的能力。例如，2023 年 7 月 7 日，印度班加羅爾 Ramaiah 理工學院 IEEE 計算智慧協會分會的一個學生團隊開發了一種名為 OurVision 的輔助設備，以幫助視障人士。

OurVision 是一款穿戴式設備，利用電腦視覺技術，包括光學字符識別 (OCR) 和機器學習，來朗讀文本並幫助用戶導航周圍環境。該項目獲得了 IEEE EPICS 的 4,400 美元資助，EPICS 是 IEEE 基金會和慷慨捐助者之間的合作夥伴關係。

光學字符識別在教育領域的採用

教育機構經常處理大量文書工作，包括學生記錄、行政文件和評估材料。 OCR 通過自動從紙質表格中提取資訊來加快數據輸入速度，減少手動數據輸入錯誤並節省時間。教育機構的圖書館和檔案館使用 OCR 對歷史文檔、手稿和研究論文進行數位化和索引，這確保了有價值的資訊的保存，同時使研究人員和學者可以輕鬆訪問這些資訊。

例如，2023 年 8 月 24 日，全球最大的 IT 基礎設施服務提供商 Kyndryl 與快速成長的線上高等教育服務提供商 USDC Projects India Pvt Ltd 達成戰略合作，以開發和管理-藝術大學管理平台。 Kyndryl 的解決方案旨在滿足大學的特定需求，融合了基於人工智慧的考試評估和評分、數位化光學字符識別以及先進的考勤系統等功能。

技術進步

深度學習技術特別是卷積神經網路和循環神經網路的整合，極大地提高了光學字符識別的準確性，這些網路使OCR系統能夠自動學習和提取圖像中的複雜特徵，從而獲得更高的識別率。 NLP 技術已被涵蓋光學字符識別系統中，以增強其對上下文和語義的理解，這使得光學字符識別能夠準確地解釋並從複雜文檔中提取有意義的資訊。

例如，2022 年 12 月 26 日，法律技術提供商 InfoTrack 正在利用 Amazon Web Services 和 ChatGPT 的先進技術來增強產權轉讓師的完成後流程。目標是加快 AP1 提交速度並確保流程中更高的準確性。

InfoTrack 利用 Amazon Web Services 的光學字符識別技術，該 OCR 技術讀取上傳的文檔，提取申請人、業主、個人代表和抵押詳細資訊等數據。隨後，ChatGPT 的軟體用於自動填充 AP1 表單並在 InfoTrack 的系統中對其進行驗證。

品質差影響市場需求

OCR 準確性很大程度上取決於輸入圖像的品質。由於解析度低、模糊、失真或噪聲等因素造成的圖像品質差可能會導致字符識別錯誤。 OCR 算法可能難以識別複雜的字體、手寫文本或風格化字符。手寫變化和藝術字體可能會導致不準確。

OCR 可能難以保留文檔的原始格式和佈局，這可能會導致維護列、表格、頁眉、頁腳和其他結構元素時出現錯誤。 OCR 系統可能會根據正在處理的文檔類型而執行不同的操作。佈局變化、字體變化和文檔特定格式都會影響識別準確性。

Overview

Global Optical Character Recognition Market reached US$ 12.2 billion in 2022 and is expected to reach US$ 31.6 billion by 2030, growing with a CAGR of 15.2% during the forecast period 2023-2030.

The ongoing changes in the adoption of digital transformation across various industries led to have massive increase in the volume of paper documents that need to be digitized and processed. OCR significantly enhances the efficiency and productivity of data by automating the extraction process and it eliminates the need for manual data entry which leads to reduced errors and saves time.

Many businesses are adopting OCR that automates various processes such as invoice processing, contract management and data extraction from various forms and this automation leads to have faster decision-making process and improved efficiency. The healthcare industry has wider adoption of OCR as it converts patient records, medical charts and prescriptions into digital format.

North America is among the growing regions in the global optical character recognition market covering more than 1/3rd of the market and the region is the hub for technological innovations. Organizations are adopting OCR which converts paper-based documents into digital format. Basically, OCR is used in research institutes and it enhances accessibility and supports online learning platforms.

Dynamics

Adoption of OCR for Visually Impaired Person

Optical character recognition has involved significant advancements in AI, machine learning and computer vision and these advancements have more accurate and reliable OCR capabilities which makes it feasible to accurately convert printed text into digital formats that can be read by assistive devices. The integration of OCR with AI and machine learning technologies enables continuous improvement of recognition accuracy.

Machine learning algorithms can adapt to different fonts, styles and languages, enhancing the OCR's ability to recognize and convert text effectively. For instance, on 7 July 2023, a team of students from the Ramaiah Institute of Technology's IEEE Computational Intelligence Society chapter in Bangalore, India, has developed an assistive device called OurVision to aid people who are visually impaired.

OurVision is a wearable device that utilizes computer vision techniques, including optical character recognition (OCR) and machine learning, to read text aloud and assist users in navigating their surroundings. The project received a grant of US$ 4,400 from EPICS in IEEE, a partnership between IEEE Foundation and generous donors.

Adoption of Optical Character Recognition in the Education Sector

Educational institutions often handle a large volume of paperwork, including student records, administrative documents and assessment materials. OCR speeds up data entry by automatically extracting information from paper-based forms, reducing manual data input errors and saving time. Libraries and archives in educational institutions use OCR to digitize and index historical documents, manuscripts and research papers and this ensures the preservation of valuable information while making it easily accessible to researchers and scholars.

For instance, on 24 August 2023, Kyndryl, the world's largest IT infrastructure services provider and USDC Projects India Pvt Ltd, a fast-growing online higher education services provider, have entered into a strategic collaboration to develop and manage a state-of-the-art university management platform. Kyndryl's solution is designed to cater to universities' specific needs, incorporating features such as AI-based exam evaluations and scoring, optical character recognition for digitization and an advanced attendance system.

Technology Advancement

The integration of deep learning techniques especially convolutional neural networks and recurrent neural networks, has greatly improved optical character recognition accuracy and these networks enable OCR systems to automatically learn and extract complex features from images, leading to higher recognition rates. NLP techniques have been incorporated into optical character recognition systems to enhance their understanding of context and semantics and this enables optical character recognition to accurately interpret and extract meaningful information from complex documents.

For instance, on 26 December 2022, InfoTrack, a legal technology provider, is leveraging advanced technologies from Amazon Web Services and ChatGPT to enhance the post-completion process for conveyancers. The goal is to accelerate AP1 submissions and ensure higher accuracy in the process.

InfoTrack utilizes Optical Character Recognition technology from Amazon Web Services and this OCR technology reads the uploaded documents, extracting data such as Applicants, Proprietors, Personal Representatives and Mortgage Details. Subsequently, ChatGPT's software is employed to automate the population of the AP1 form and validate it within InfoTrack's system.

Poor Quality Affecting the Market Demand

OCR accuracy is highly dependent on the quality of the input image. Poor image quality due to factors like low resolution, blurriness, distortion or noise can lead to errors in character recognition. OCR algorithms may struggle with recognizing complex fonts, handwritten text or stylized characters. Handwriting variations and artistic fonts can result in inaccuracies.

OCR may have difficulty preserving the original formatting and layout of the document and this can lead to errors in maintaining columns, tables, headers, footers and other structural elements. OCR systems may perform differently based on the type of document being processed. Layout variations, font changes and document-specific formatting can affect recognition accuracy.

Segment Analysis

The global optical character recognition market is segmented based type, application, end-user and region.

Digitalized Content and Leading Software Solutions Increases Market Demand Software is expected to be the major segment fueling the market growth with a share of about 1/3rd during the forecast period. As more content becomes digitized, there is a growing need to convert printed and handwritten documents into machine-readable text. Optical character recognition software plays a crucial role in this digital transformation process.

Optical character recognition software that supports multiple languages is in high demand as companies operate on a global scale. The ability to recognize and process text in different languages is essential for accurate data extraction and translation.

For instance, on 25 October 2022, Inspur Information, a leading IT infrastructure solutions provider, collaborated with Upstage, a Korean AI company, to build an advanced AI server architecture platform. Upstage is developing an AI-based B2B no-code/low-code software solution called AI Pack, with a core application named OCR Pack for document recognition.

Geographical Penetration

The Rising Digitalization and Partnerships in Asia-Pacific

Asia-Pacific is among the major regions in the global optical character recognition market covering around 1/4th of the market in 2022. The region actively pursuing digital transformation initiatives across various sectors, including government, finance, healthcare and education. OCR plays a crucial role in digitizing and processing large volumes of paper-based documents, contributing to overall digitalization efforts.

For instance, on 24 August 2022, Tata Power Delhi Distribution Ltd implemented an AI-based forensic meter reading solution in collaboration with data capture and AI developer Anyline. This solution employs optical character recognition technology to enhance meter reading accuracy and reduce non-technical losses for the North Delhi region. The partnership with Anyline reflects Tata Power-DDL's commitment to leveraging advanced technologies to benefit its customers.

Competitive Landscape

The major global players in the market include: ABBYY, Adobe, Captricity Inc., Anyline Gmbh, ATAPY Software, Google LLC, IRIS S.A, Microsoft, NAVER Crop and Open Text Corporation.

COVID-19 Impact Analysis

The pandemic accelerated the adoption of remote work and digital transformation across industries. As organizations shifted to remote operations, the demand for digitizing documents and automating data extraction through OCR increased. OCR played a crucial role in enabling remote workers to access and process information from scanned or printed documents.

The healthcare sector experienced an increased need for efficient data processing due to the pandemic. OCR helped healthcare professionals digitize and extract valuable information from medical records, test results and other documents, facilitating faster decision-making and patient care. Researchers and public health agencies needed to analyze a vast amount of data related to COVID-19 cases, treatments and outcomes.

AI Impact

AI-powered OCR systems use advanced machine learning algorithms to recognize characters and patterns in images and this results in higher accuracy rates compared to traditional OCR methods, especially when dealing with complex fonts, handwritten text or degraded images. AI-driven OCR solutions can support a wider range of languages and scripts. Machine learning models can be trained on diverse language datasets, enabling OCR systems to accurately recognize text in various languages.

AI-based OCR can adapt and learn from new data and this adaptability allows the system to improve its accuracy over time as it encounters more diverse examples, making it suitable for applications with evolving content. AI-powered OCR systems can analyze context and semantics to better interpret the meaning of text and this contextual understanding enables better comprehension of documents and supports more intelligent data extraction.

For instance, on 16 August 2023, Tricentis' Vision AI, an AI-based test automation feature in the company's flagship product Tricentis Tosca, the method and system for single pass OCR was invented by David Colwell. Vision AI employs a neural network comprising multiple algorithms to simultaneously scan multiple images around text and this advancement significantly improves the speed of OCR technology, reducing response time from an average of one second to just 40 milliseconds.

Russia- Ukraine War Impact

The conflict led to the closure or disruption of key transportation routes between Russia and Ukraine. Border closures, checkpoints and conflict zones have hindered the movement of goods by road, rail and even air in some cases. The conflict has disrupted supply chains that rely on the efficient movement of goods between Russia, Ukraine and neighboring countries. Companies that source raw materials, components or finished products from these regions have had to seek alternative routes or suppliers.

Trade between Russia and Ukraine, as well as with other countries, has been affected. Export and import activities have faced delays, restrictions and uncertainty due to the conflict and this has impacted industries dependent on cross-border trade. Transportation costs have risen due to the need for alternative routes, longer transit times and security measures. Uncertainty about the situation has also made long-term logistics planning more challenging.

By Type

Software
Services

By Application

Retail
BFSI
Government
IT Telecom
Transport and Logistics
Healthcare
Others

By End-User

By Region

North America
- U.S.
- Canada
- Mexico

Europe
- Germany
- UK
- France
- Italy
- Russia
- Rest of Europe

South America
- Brazil
- Argentina
- Rest of South America

Asia-Pacific
- China
- India
- Japan
- Australia
- Rest of Asia-Pacific

Middle East and Africa

Key Developments

On 31 July 2023, Bluevine, a prominent provider of solutions for small business banking, unveiled its latest offering: an accounts payable solution aimed at simplifying the management of business payments for owners and their teams within their Bluevine Business Checking accounts. The platform employs optical character recognition to extract data from the bills, presenting them to users for quick verification and confirmation.
On 2 August 2023, Viaccess-Orca (VO), Multi-Development and Construction Corporation (MDCC), Jose Paolo Calma, introduced Homeqube, a blockchain and artificial intelligence (AI)-driven homebuilding platform. The platform includes optical character recognition for automatic lot area plotting, agile design capabilities and auto-generation of essential documents before move-in.
On 11 July 2023, Smart Data Solutions expanded its operations into India by establishing a Center of Excellence in Chennai and its expansion reflects the company's commitment for enhancing its capabilities and services in the region. The Center of Excellence is equipped with advanced technologies, including Optical Character Recognition to streamline data processing and deliver efficient solutions.

Why Purchase the Report?

To visualize the global optical character recognition market segmentation based on type, application, end-user and region, as well as understand key commercial assets and players.
Identify commercial opportunities by analyzing trends and co-development.
Excel data sheet with numerous data points of optical character recognition market-level with all segments.
PDF report consists of a comprehensive analysis after exhaustive qualitative interviews and an in-depth study.
Product mapping available as excel consisting of key products of all the major players.

The global optical character recognition market report would provide approximately 61 tables, 59 figures and 185 pages.

Target Audience 2023

Manufacturers/ Buyers
Industry Investors/Investment Bankers
Research Professionals
Emerging Companies

1. Methodology and Scope

1.1. Research Methodology
1.2. Research Objective and Scope of the Report

2. Definition and Overview

3. Executive Summary

3.1. Snippet by Type
3.2. Snippet by Application
3.3. Snippet by End-User
3.4. Snippet by Region

4. Dynamics

4.1. Impacting Factors
- 4.1.1. Drivers
  - 4.1.1.1. Adoption of OCR for Visually Impaired Person
  - 4.1.1.2. Adoption of Optical Character Recognition in the Education Sector
  - 4.1.1.3. Technology Advancement
- 4.1.2. Restraints
  - 4.1.2.1. Poor Quality Affecting the Demand of Market
- 4.1.3. Opportunity
- 4.1.4. Impact Analysis

5. Industry Analysis

5.1. Porter's Five Force Analysis
5.2. Supply Chain Analysis
5.3. Pricing Analysis
5.4. Regulatory Analysis
5.5. Russia-Ukraine War Impact Analysis
5.6. DMI Opinion

6. COVID-19 Analysis

6.1. Analysis of COVID-19
- 6.1.1. Scenario Before COVID
- 6.1.2. Scenario During COVID
- 6.1.3. Scenario Post COVID
6.2. Pricing Dynamics Amid COVID-19
6.3. Demand-Supply Spectrum
6.4. Government Initiatives Related to the Market During Pandemic
6.5. Manufacturers Strategic Initiatives
6.6. Conclusion

7. By Type

7.1. Introduction
- 7.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 7.1.2. Market Attractiveness Index, By Type
7.2. Software*
- 7.2.1. Introduction
- 7.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
7.3. Services

8. By Application

8.1. Introduction
- 8.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 8.1.2. Market Attractiveness Index, By Application
8.2. Retail*
- 8.2.1. Introduction
- 8.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
8.3. BFSI
8.4. Government
8.5. IT Telecom
8.6. Transport and Logistics
8.7. Healthcare
8.8. Others

9. By End-User

9.1. Introduction
- 9.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 9.1.2. Market Attractiveness Index, By End-User
9.2. B2B*
- 9.2.1. Introduction
- 9.2.2. Market Size Analysis and Y-o-Y Growth Analysis (%)
9.3. B2C

10. By Region

10.1. Introduction
- 10.1.1. Market Size Analysis and Y-o-Y Growth Analysis (%), By Region
- 10.1.2. Market Attractiveness Index, By Region
10.2. North America
- 10.2.1. Introduction
- 10.2.2. Key Region-Specific Dynamics
- 10.2.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 10.2.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.2.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.2.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.2.6.1. U.S.
  - 10.2.6.2. Canada
  - 10.2.6.3. Mexico
10.3. Europe
- 10.3.1. Introduction
- 10.3.2. Key Region-Specific Dynamics
- 10.3.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 10.3.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.3.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.3.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.3.6.1. Germany
  - 10.3.6.2. UK
  - 10.3.6.3. France
  - 10.3.6.4. Italy
  - 10.3.6.5. Russia
  - 10.3.6.6. Rest of Europe
10.4. South America
- 10.4.1. Introduction
- 10.4.2. Key Region-Specific Dynamics
- 10.4.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 10.4.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.4.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.4.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.4.6.1. Brazil
  - 10.4.6.2. Argentina
  - 10.4.6.3. Rest of South America
10.5. Asia-Pacific
- 10.5.1. Introduction
- 10.5.2. Key Region-Specific Dynamics
- 10.5.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 10.5.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.5.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User
- 10.5.6. Market Size Analysis and Y-o-Y Growth Analysis (%), By Country
  - 10.5.6.1. China
  - 10.5.6.2. India
  - 10.5.6.3. Japan
  - 10.5.6.4. Australia
  - 10.5.6.5. Rest of Asia-Pacific
10.6. Middle East and Africa
- 10.6.1. Introduction
- 10.6.2. Key Region-Specific Dynamics
- 10.6.3. Market Size Analysis and Y-o-Y Growth Analysis (%), By Type
- 10.6.4. Market Size Analysis and Y-o-Y Growth Analysis (%), By Application
- 10.6.5. Market Size Analysis and Y-o-Y Growth Analysis (%), By End-User

11. Competitive Landscape

11.1. Competitive Scenario
11.2. Market Positioning/Share Analysis
11.3. Mergers and Acquisitions Analysis

12. Company Profiles

12.1. ABBYY*
- 12.1.1. Company Overview
- 12.1.2. Product Portfolio and Description
- 12.1.3. Financial Overview
- 12.1.4. Key Developments
12.2. Adobe
12.3. Captricity Inc.
12.4. Anyline Gmbh
12.5. ATAPY Software
12.6. Google LLC
12.7. IRIS S.A
12.8. Microsoft
12.9. NAVER Crop
12.10. Open Text Corporation

LIST NOT EXHAUSTIVE