影像識別市場－2025-2030年預測

影像識別市場預計將從 2025 年的 573.6 億美元快速成長到 2030 年的 1,092.36 億美元，複合年成長率為 13.75%。

影像識別市場是人工智慧 (AI) 和電腦視覺的關鍵領域，它使系統能夠利用卷積類神經網路(CNN) 和深度學習模型等先進演算法來解讀和分析影像和影片中的視覺資料。這項技術正在推動創新，並增強醫療保健、汽車、零售和安防等行業的自動化和決策能力。其應用領域包括醫學影像分析、自動駕駛、庫存管理和生物識別，而這些應用都受到視覺數據量不斷成長和人工智慧技術進步的推動。

本報告檢驗了當前市場需求、供應和銷售趨勢以及影響市場格局的最新發展。報告全面分析了關鍵促進因素、阻礙因素和機遇，並詳細說明了區域產業趨勢、政策和法規，以幫助相關人員深入了解法規結構和市場趨勢。

我們的競爭情報是基於二手研究，包括產業調查、分析師報告、投資者報告、新聞稿和學術期刊，識別主要企業及其收入貢獻。市場規模的計算採用由下而上和自上而下的方法，並結合全球價值鏈各相關人員的意見檢驗。我們全面的市場分析設計整合了多來源資料和專有資料集，並透過多方面檢驗，提供精準的預測。分析結果以文字、圖表和圖形的形式呈現，以便於理解。預計全球市場規模將在2025年達到530億美元，到2032年成長至1,268億美元，複合年成長率（CAGR）為15.1%。主要參與者包括Google、亞馬遜、微軟、Meta AI和英偉達。

主要亮點

增強型神經網路提高了準確率和速度，推動了其應用。影片內容的爆炸性成長是推動這項需求的主要因素，預計到2026年，影片流量將佔網路流量的82%。醫療保健、汽車和零售業正在利用影像識別開發變革性應用。然而，隱私法規和倫理問題，特別是關於臉部辨識技術的倫理問題，限制了其應用。

成長要素

人工智慧技術的進步，例如Meta AI於2024年發布的DINOv2模型，正在增強自監督學習能力，降低成本並提高可擴展性。 5G推動了智慧型手機和物聯網視覺數據的爆炸性成長，這需要先進的處理工具。特斯拉的完全自動駕駛和亞馬遜的「即拿即走」等工業應用正在推動人工智慧的普及。包括歐盟2024年人工智慧法案在內的政府舉措，正在支持符合監管規定的安全應用。

阻礙因素

2024 年 Clearview AI 資料抓取醜聞以及 GDPR/CCPA 法規等爭議事件引發了人們對隱私的擔憂，並限制了臉部辨識技術的應用。 GPU 和雲端基礎設施的高昂運算成本也為中型企業帶來了挑戰。正如 NIST 在 2023 年的一項研究中指出的，複雜環境下的資料集偏差和準確性問題會降低技術的可靠性。

細分分析

按組件分類：軟體佔據主導地位，以Google 的 Vision AI 和 Meta 的 DINOv2 等擴充性框架為主導，推動了通用應用程式的發展。

以部署方式來看：由 AWS Rekognition 和 Azure 電腦視覺支援的雲端解決方案處於主導，提供了擴充性和成本效益。

按最終用戶分類：通訊和科技產業正在經歷快速成長，Meta 和位元組跳動等公司正在利用影像識別技術進行內容審核和擴增實境。

區域分析

北美主導，主要得益於美國在人工智慧領域的投資，預計到2024年將超過200億美元，以及醫療保健和零售業強大的生態系統。亞太地區發展迅速，這得益於中國的智慧城市計畫和印度的數位化擴張。歐洲也在穩步推進，2024年《人工智慧法案》的頒布旨在支持符合倫理規範的應用。

本報告為行業專業人士提供關於發展趨勢、監管法規和競爭機會的深入見解，重點關注人工智慧驅動和產業專用的應用領域的機遇，同時探討隱私和成本方面的挑戰。嚴謹的調查方法確保了對這一變革性人工智慧領域策略決策的可靠預測。

本報告的主要優勢：

• 深入分析：取得以客戶群、政府政策和社會經濟因素、消費者偏好、垂直產業和其他細分市場為重點的深入市場洞察，涵蓋主要地區和新興地區。
• 競爭格局：了解主要企業採取的策略舉措，並了解透過正確的策略打入市場的潛力。
• 市場促進因素與未來趨勢：探索動態因素和關鍵市場趨勢，以及它們將如何塑造未來的市場發展。
• 可執行的建議：利用洞察力為策略決策提供訊息，從而在動態環境中開拓新的業務管道和收入來源。
• 受眾範圍廣：對新興企業、研究機構、顧問公司、中小企業和大型企業都有益處且經濟高效。

它是用來做什麼的？

產業與市場洞察、商業機會評估、產品需求預測、打入市場策略、地理擴張、資本投資決策、法律規範及其影響、新產品開發、競爭影響

分析範圍

• 歷史資料（2022-2024 年）和預測資料（2025-2030 年）
• 成長機會、挑戰、供應鏈前景、法規結構、客戶行為和趨勢分析
• 競爭對手定位、策略和市場佔有率分析
• 按業務板塊和地區（國家）分類的收入成長和預測分析
• 公司概況（策略、產品、財務資訊、關鍵趨勢等）

目錄

第1章執行摘要

第2章市場概述

• 市場概覽
• 市場定義
• 分析範圍
• 市場區隔

第3章 商業情境

• 市場促進因素
• 市場限制
• 市場機遇
• 波特五力分析
• 產業價值鏈分析
• 政策和法規
• 策略建議

第4章 技術展望

第5章影像識別市場（按組件分類）

• 介紹
• 硬體
• 軟體
• 服務

第6章影像識別市場：依部署方式分類

• 介紹
• 本地部署
• 雲

第7章影像識別市場：依公司規模分類

• 介紹
• 小規模企業
• 中型公司
• 主要企業

第8章 按應用程式分類的影像識別市場

• 介紹
• 臉部辨識
• 目標識別
• 光學字元辨識（OCR）
• 其他

第9章 依最終用戶分類的影像識別市場

• 介紹
• 資訊科技/通訊
• 銀行、金融服務和保險業 (BFSI)
• 零售
• 政府
• 媒體與娛樂
• 醫療保健
• 其他

第10章 區域影像識別市場

• 介紹
• 北美洲
  • 美國
  • 加拿大
  • 墨西哥
• 南美洲
  • 巴西
  • 阿根廷
  • 其他
• 歐洲
  • 德國
  • 法國
  • 英國
  • 西班牙
  • 其他
• 中東和非洲
  • 沙烏地阿拉伯
  • 阿拉伯聯合大公國
  • 以色列
  • 其他
• 亞太地區
  • 中國
  • 印度
  • 日本
  • 韓國
  • 印尼
  • 泰國
  • 台灣
  • 其他

第11章 競爭格局與分析

• 主要企業和策略分析
• 市佔率分析
• 企業合併、協議、商業合作
• 競爭對手儀錶板

第12章：公司簡介

• Qualcomm Technologies, Inc.
• Microsoft Corporation
• IBM Corporation
• Google Inc.
• NVIDIA Corporation
• Amazon Web Services Inc.
• Hitachi Ltd.
• Clarifai Inc.
• Intel Corporation
• Huawei Technologies Co., Ltd.
• NEC Corporation

第13章附錄

• 貨幣
• 先決條件
• 基準年和預測年時間表
• 相關人員的主要收益
• 分析方法
• 簡稱

The Image Recognition Market will soar from USD 57.360 billion in 2025 to USD 109.236 billion by 2030, fueled by a 13.75% compound annual growth rate (CAGR).

The image recognition market, a critical segment of artificial intelligence (AI) and computer vision, enables systems to interpret and analyze visual data from images and videos using advanced algorithms and deep learning models like convolutional neural networks (CNNs). This technology drives innovation across healthcare, automotive, retail, and security, enhancing automation and decision-making. Its applications include medical imaging analysis, autonomous driving, inventory management, and biometric authentication, fueled by the growing volume of visual data and AI advancements.

This research examines current trends in demand, supply, and sales, alongside recent developments shaping the market. It provides a comprehensive analysis of key drivers, restraints, and opportunities, detailing industry trends, policies, and regulations across geographical regions to equip stakeholders with insights into the regulatory framework and market dynamics.

Competitive intelligence identifies major players and their revenue contributions, derived from secondary research, including industry studies, analyst reports, investor presentations, press releases, and journals. Market size was determined using bottom-up and top-down methodologies, validated with stakeholder inputs from the global value chain. Comprehensive market engineering integrated multi-source data and proprietary datasets via triangulation for accurate forecasting. Insights are presented through narratives, charts, and graphics for efficient comprehension. The global market is projected to reach USD 53.0 billion in 2025, growing at a CAGR of 15.1% to USD 126.8 billion by 2032. Key players include Google, Amazon, Microsoft, Meta AI, and NVIDIA, among others.

Key Highlights

Enhanced neural networks improve accuracy and speed, driving adoption. Surging video content, expected to account for 82% of internet traffic by 2026, fuels demand. Healthcare, automotive, and retail leverage image recognition for transformative applications. Privacy regulations and ethical concerns, particularly for facial recognition, limit deployment.

Growth Drivers

AI advancements, such as Meta AI's DINOv2 model in 2024, enhance self-supervised learning, reducing costs and boosting scalability. The proliferation of visual data from smartphones and IoT, supported by 5G, necessitates advanced processing tools. Industry applications, like Tesla's Full Self-Driving and Amazon's Just Walk Out, drive adoption. Government initiatives, including the EU's 2024 AI Act, support compliant security applications.

Restraints

Privacy concerns, intensified by 2024 controversies like Clearview AI's data scraping, and GDPR/CCPA regulations restrict facial recognition. High computational costs for GPUs and cloud infrastructure challenge mid-sized firms. Bias in datasets, noted in NIST's 2023 study, and accuracy issues in complex environments hinder reliability.

Segmentation Analysis

By Component: Software dominates, driven by scalable frameworks like Google's Vision AI and Meta's DINOv2 for versatile applications.

By Deployment Model: Cloud solutions lead, supported by AWS Rekognition and Azure Computer Vision, offering scalability and cost-efficiency.

By End-User: Communication and technology commands rapid growth, with Meta and ByteDance using image recognition for content moderation and AR.

Regional Analysis

North America leads, driven by U.S. AI investments exceeding $20 billion in 2024 and robust ecosystems in healthcare and retail. Asia Pacific grows rapidly, fueled by China's smart city initiatives and India's digital expansion. Europe advances with the 2024 AI Act supporting ethical deployments.

Key Developments

In October 2023, Klarna launched Shopping Lens, an AI-powered tool for visual product search in retail. In 2024, Meta AI's DINOv2 advanced self-supervised learning, enhancing model efficiency.

This report equips industry experts with insights into trends, regulations, and competitive dynamics, highlighting opportunities in AI-driven and industry-specific applications while addressing privacy and cost challenges. The rigorous methodology ensures reliable projections for strategic decision-making in this transformative AI sector.

Key Benefits of this Report:

• Insightful Analysis: Gain detailed market insights covering major as well as emerging geographical regions, focusing on customer segments, government policies and socio-economic factors, consumer preferences, industry verticals, and other sub-segments.
• Competitive Landscape: Understand the strategic maneuvers employed by key players globally to understand possible market penetration with the correct strategy.
• Market Drivers & Future Trends: Explore the dynamic factors and pivotal market trends and how they will shape future market developments.
• Actionable Recommendations: Utilize the insights to exercise strategic decisions to uncover new business streams and revenues in a dynamic environment.
• Caters to a Wide Audience: Beneficial and cost-effective for startups, research institutions, consultants, SMEs, and large enterprises.

What do businesses use our reports for?

Industry and Market Insights, Opportunity Assessment, Product Demand Forecasting, Market Entry Strategy, Geographical Expansion, Capital Investment Decisions, Regulatory Framework & Implications, New Product Development, Competitive Intelligence

Report Coverage:

• Historical data from 2022 to 2024 & forecast data from 2025 to 2030
• Growth Opportunities, Challenges, Supply Chain Outlook, Regulatory Framework, and Trend Analysis
• Competitive Positioning, Strategies, and Market Share Analysis
• Revenue Growth and Forecast Assessment of segments and regions including countries
• Company Profiling (Strategies, Products, Financial Information, and Key Developments among others.

Segmentation

By Component

• Hardware
• Software
• Services

By Deployment

• On-Premise
• Cloud

By Enterprise Size

• Small
• Medium
• Large

By Application

• Facial Recognition
• Object Recognition
• Optical Character Recognition (OCR)
• Others

By End-User

• IT & Telecommunication
• BFSI
• Retail
• Government
• Media & Entertainment
• Healthcare
• Others

By Geography

• North America
• USA
• Canada
• Mexico
• South America
• Brazil
• Argentina
• Others
• Europe
• Germany
• France
• United Kingdom
• Spain
• Others
• Middle East and Africa
• Saudi Arabia
• UAE
• Israel
• Others
• Asia Pacific
• China
• India
• Japan
• South Korea
• Indonesia
• Thailand
• Taiwan
• Others

TABLE OF CONTENTS

1. EXECUTIVE SUMMARY

2. MARKET SNAPSHOT

• 2.1. Market Overview
• 2.2. Market Definition
• 2.3. Scope of the Study
• 2.4. Market Segmentation

3. BUSINESS LANDSCAPE

• 3.1. Market Drivers
• 3.2. Market Restraints
• 3.3. Market Opportunities
• 3.4. Porter's Five Forces Analysis
• 3.5. Industry Value Chain Analysis
• 3.6. Policies and Regulations
• 3.7. Strategic Recommendations

4. TECHNOLOGICAL OUTLOOK

5. IMAGE RECOGNITION MARKET BY COMPONENT

• 5.1. Introduction
• 5.2. Hardware
• 5.3. Software
• 5.4. Services

6. IMAGE RECOGNITION MARKET BY DEPLOYMENT

• 6.1. Introduction
• 6.2. On-Premise
• 6.3. Cloud

7. IMAGE RECOGNITION MARKET BY ENTERPRISE SIZE

• 7.1. Introduction
• 7.2. Small
• 7.3. Medium
• 7.4. Large

8. IMAGE RECOGNITION MARKET BY APPLICATION

• 8.1. Introduction
• 8.2. Facial Recognition
• 8.3. Object Recognition
• 8.4. Optical Character Recognition (OCR)
• 8.5. Others

9. IMAGE RECOGNITION MARKET BY END-USER

• 9.1. Introduction
• 9.2. IT & Telecommunication
• 9.3. BFSI
• 9.4. Retail
• 9.5. Government
• 9.6. Media & Entertainment
• 9.7. Healthcare
• 9.8. Others

10. IMAGE RECOGNITION MARKET BY GEOGRAPHY

• 10.1. Introduction
• 10.2. North America
  • 10.2.1. USA
  • 10.2.2. Canada
  • 10.2.3. Mexico
• 10.3. South America
  • 10.3.1. Brazil
  • 10.3.2. Argentina
  • 10.3.3. Others
• 10.4. Europe
  • 10.4.1. Germany
  • 10.4.2. France
  • 10.4.3. United Kingdom
  • 10.4.4. Spain
  • 10.4.5. Others
• 10.5. Middle East and Africa
  • 10.5.1. Saudi Arabia
  • 10.5.2. UAE
  • 10.5.3. Israel
  • 10.5.4. Others
• 10.6. Asia Pacific
  • 10.6.1. China
  • 10.6.2. India
  • 10.6.3. Japan
  • 10.6.4. South Korea
  • 10.6.5. Indonesia
  • 10.6.6. Thailand
  • 10.6.7. Taiwan
  • 10.6.8. Others

11. COMPETITIVE ENVIRONMENT AND ANALYSIS

• 11.1. Major Players and Strategy Analysis
• 11.2. Market Share Analysis
• 11.3. Mergers, Acquisitions, Agreements, and Collaborations
• 11.4. Competitive Dashboard

12. COMPANY PROFILES

• 12.1. Qualcomm Technologies, Inc.
• 12.2. Microsoft Corporation
• 12.3. IBM Corporation
• 12.4. Google Inc.
• 12.5. NVIDIA Corporation
• 12.6. Amazon Web Services Inc.
• 12.7. Hitachi Ltd.
• 12.8. Clarifai Inc.
• 12.9. Intel Corporation
• 12.10. Huawei Technologies Co., Ltd.
• 12.11. NEC Corporation

13. APPENDIX

• 13.1. Currency
• 13.2. Assumptions
• 13.3. Base and Forecast Years Timeline
• 13.4. Key benefits for the stakeholders
• 13.5. Research Methodology
• 13.6. Abbreviations