電腦視覺：市場佔有率分析、行業趨勢、統計數據和成長預測（2025-2030 年）

電腦視覺市場規模預計在 2025 年達到 284 億美元，預計到 2030 年將達到 586 億美元，預測期（2025-2030 年）複合年成長率為 16%。

成長的驅動力來自速度更快的邊緣人工智慧晶片組，這些晶片組將推理任務從雲端伺服器轉移到設備端處理器。此外，工廠勞動力短缺、視覺引導機器人的日益普及以及亞太地區出口型工廠廣泛採用工業相機也是推動需求成長的因素。同時，汽車原始設備製造商 (OEM) 正在部署多攝影機高級駕駛輔助系統 (ADAS) 套件，以符合歐盟通用安全法規 II (GDPR II) 的要求，從而將監管期限轉化為嵌入式視覺感測器的批量出貨。先進晶片的出口限制正在收緊對二線經濟體的供應，刺激國內半導體投資並改變市場競爭動態。

全球電腦視覺市場趨勢與洞察

製造業中視覺引導機器人技術的應用日益普及

工廠管理者正將自動化程度提升到超越常規取放任務的水平，配備先進視覺系統的協作機器人如今能夠執行以往需要人工才能完成的組裝​​檢驗和缺陷檢測任務。美國國家標準與技術研究院 (NIST) 將機器視覺列為實現機器人靈活性的關鍵支柱，尤其是在半導體和生物製造無塵室等對亞微米級公差要求極高的領域。現代汽車的電子產品生產線在部署了能夠利用混合資料集重新訓練演算法並保持模型更新而無需停產的移動機器人後，一次合格率顯著提高。視覺引導的協作機器人也為預測性維護提供了支持，能夠在故障導致生產計劃中斷之前識別工具產量比率。它們的投資回報率超過了人形機器人，因此在建築和農業等以往因環境非結構化而難以自動化的行業中得到了更廣泛的應用。這些轉變共同重塑了工廠的經濟格局，減少了對稀缺技術純熟勞工的依賴，並提高了多品種生產線的產量穩定性。

受監管行業嚴格的品管要求

由於反覆的召回事件暴露了人工檢測的局限性，監管機構現在認為自動化光學檢測至關重要。歐盟通用安全法規II要求汽車製造商自2024年7月起必須配備行人偵測攝影機和緊急煞車邏輯，這迫使一級供應商圍繞視覺模型重新設計電控系統。製藥公司正在部署深度學習視覺技術來檢驗泡殼包裝的完整性和標籤的準確性。食品加工商正在整合康耐視In-Sight感測器，以實現100%的異物偵測率，從而減少污染召回並加強審核追蹤。環保機構也同樣要求提供廢水合規性的持續視訊證據，這使得視覺系統從一項可有可無的支出轉變為一項影響採購決策的風險緩解資產。

複雜的系統整合要求

傳統工廠生產線依賴專有的現場匯流排通訊協定和非屏蔽線路，這使得用攝影機系統直接取代人工偵測變得複雜。惡劣工作環境中的振動和電磁雜訊會降低影像保真度，需要堅固耐用的光學元件和較長的校準週期。當多感測器融合技術加入雷射雷達或熱成像輸入時，整合商必須同步不同即時作業系統之間的資料流，這會延長缺乏內部專業知識的中小型企業的部署週期。客製化中間件和安全認證會增加計劃預算，超越最初的投資報酬率預期，從而阻礙技術的普及應用。

細分市場分析

到2024年，硬體將佔電腦視覺市場收入的68.0%，這主要得益於企業採購工業相機、照明設備和專用處理器來改造生產線。其中，邊緣AI加速器到2030年將以24.5%的複合年成長率成長，成為所有子組件中成長最快的。相機模組仍將佔據最大佔有率，但隨著智慧感測器整合影像擷取和推理功能，降低線纜成本和延遲，其市場佔有率將會下降。光學設備供應商將受益於高光譜遙測鏡頭，這種鏡頭能夠檢測可見頻譜以外的材料特徵，應用於農業和回收領域。在軟體方面，容器化推理堆疊和中介軟體的年度訂閱預算高於永久授權演算法，這反映出模型正在向持續重新調優轉變。預計到2030年，電腦視覺硬體市場規模將超過340億美元，主要得益於汽車和電子產品原始設備製造商（OEM）的強勁資本支出。

2024年，軟體平台支出將佔總支出的32.0%，並隨著企業優先考慮資料管道和DevOps整合而非一次性配置而穩定成長。邊緣編配框架有助於將模型更新分發到數千個終端，從而將設備叢集轉變為自適應感測器網路。這一轉變與日益成長的網路安全擔憂不謀而合，這些擔憂促使企業傾向於本地資料處理和透明的審核追蹤。因此，系統整合商正在提供承包解決方案，以縮短沒有專門機器學習團隊的中型工廠的價值實現時間，從而擴大電腦視覺市場的潛在需求。

電腦視覺市場按組件（硬體和軟體）、最終用戶產業（生命科學、汽車製造、零售和電子商務、物流和倉儲等）以及地區進行細分。

區域分析

到2024年，亞太地區將佔電腦視覺市場收入的41.0%。受機器人技術快速普及的推動，中國工業相機銷售額預計將從2023年的185億元人民幣成長28.35%至2024年的207億元。日本晶片代工廠和韓國智慧型手機OEM廠商將維持對晶圓級AOI工具的強勁需求，而印度將擴大精密農業試點規模，以緩解氣候變遷帶來的糧食供應壓力。政府的綠色工廠計劃為智慧相機維修津貼補貼，在宏觀經濟逆風的情況下，支撐了穩定的資本投資。限制高階GPU出口的出口管制政策正促使本地晶圓廠轉向國產加速器，逐步提升該地區的自主研發能力。

到2030年，中東地區將以17.2%的複合年成長率成為成長最快的地區。沙烏地阿拉伯設立了1000億美元的人工智慧基金，而阿拉伯聯合大公國的目標是到2031年躋身全球十大人工智慧中心之列。在利雅德和杜拜，政府支持的智慧城市建設正在推動大量配備邊緣分析技術的監視錄影機的採購，以保障交通流量和關鍵基礎設施的安全。同時，港口和自由區在物流自動化方面的投資也將進一步擴大沿岸地區的電腦視覺市場。

在北美，美國國家公路交通安全管理局 (NHTSA) 即將實施的自動煞車強制令推動了高級駕駛輔助系統 (ADAS) 攝影機的持續出貨，而美國國防部也在資助以視覺為中心的自動駕駛計劃並保持強勁的採購勢頭。然而，人才短缺和晶片出口受限正在減緩近期的成長，凸顯了本地化培訓計畫和多樣化晶片供應的必要性。

其他福利：

• Excel格式的市場預測（ME）表
• 3個月的分析師支持

目錄

第1章 引言

• 研究假設和市場定義
• 調查範圍

第2章調查方法

第3章執行摘要

第4章 市場情勢

• 市場概覽
• 市場促進因素
  • 製造業中視覺引導機器人的應用日益普及
  • 受監管行業必須遵守嚴格的品管義務
  • 車載ADAS攝影機整合激增
  • 邊緣AI晶片組可降低裝置端視覺的延遲和功耗。
  • 高光譜遙測和神經形態感測器開啟了新的應用場景
• 市場限制
  • 複雜的系統整合要求
  • 熟練的電腦視覺工程師短缺
  • 數據標註成本不斷上升
  • 對先進視覺處理器的出口限制
• 價值/供應鏈分析
• 監管環境
• 技術展望
• 波特五力模型
  • 新進入者的威脅
  • 買方的議價能力
  • 供應商的議價能力
  • 替代品的威脅
  • 競爭對手之間的競爭

第5章 市場規模與成長預測

• 按組件
  • 硬體
    • 相機
    • 處理器（GPU/ASIC/FPGA）
    • 光學與照明
  • 軟體
    • 傳統演算法
    • 深度學習框架
    • 邊緣中介軟體
• 按最終用戶行業分類
  • 生命科學
  • 製造業
    • 電子組裝
    • 飲食
    • 包裹
  • 國防與安全
  • 車
    • ADAS
    • 自動駕駛汽車
  • 零售與電子商務
  • 物流/倉儲
  • 農業和林業
  • 其他行業
• 按地區
  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 法國
    • 義大利
    • 西班牙
    • 俄羅斯
    • 其他歐洲地區
  • 亞太地區
    • 中國
    • 日本
    • 韓國
    • 印度
    • ASEAN
    • 澳洲和紐西蘭
    • 亞太其他地區
  • 中東
    • GCC
    • 土耳其
    • 其他中東地區
  • 非洲
    • 南非
    • 奈及利亞
    • 其他非洲地區
  • 南美洲
    • 巴西
    • 阿根廷
    • 其他南美洲

第6章 競爭情勢

• 市場集中度
• 策略趨勢
• 市佔率分析
• 公司簡介
  • Intel Corporation
  • Cognex Corporation
  • Keyence Corporation
  • Sony Group Corp.
  • NVIDIA Corporation
  • Omron Corporation
  • Basler AG
  • Teledyne FLIR LLC
  • Qualcomm Inc.
  • Google LLC
  • Advanced Micro Devices（AMD）
  • Adlink Technology Inc.
  • Hikvision Robotics
  • Stemmer Imaging AG
  • Dahua Technology
  • Zebra Technologies
  • Amazon Web Services（AWS）
  • Clarifai Inc.
  • Allied Vision Technologies
  • OpenCV.ai
  • Matrox Imaging

第7章 市場機會與未來展望

The Computer Vision Market size is estimated at USD 28.40 billion in 2025, and is expected to reach USD 58.60 billion by 2030, at a CAGR of 16% during the forecast period (2025-2030).

Growth pivots around faster edge-AI chipsets that move inference from cloud servers to on-device processors, a shift encouraged by stricter automotive and manufacturing regulations that insist on real-time, auditable inspection data. Demand also benefits from acute labor shortages on factory floors, increasing use of vision-guided robotic,s and wider industrial camera uptake across Asia-Pacific's export-oriented plant,s Sohu. Simultaneously, automotive OEMs implement multi-camera ADAS suites to comply with EU General Safety Regulation II, turning regulatory deadlines into volume shipments for embedded visionsensorsr. Export-control rules on advanced chips tighten supply for Tier 2 economies, yet they accelerate domestic semiconductor investments, altering competitive dynamics in the computer vision market.

Global Computer Vision Market Trends and Insights

Rising Adoption of Vision-Guided Robotics in Manufacturing

Plant managers escalate automation beyond pick-and-place routines as collaborative robots equipped with advanced vision now handle assembly verification and defect inspection that previously required human eyes. NIST classifies machine vision as an enabling pillar for robotic flexibility, especially in semiconductor and biomanufacturing cleanrooms where sub-micron tolerances are non-negotiable.Hyundai's electronics lines report higher first-pass yield after introducing mobile robots that retrain algorithms on mixed data sets, keeping models current without halting production. Vision-guided cobots also underpin predictive maintenance, identifying tool wear before failures disrupt schedules. Return on investment outperforms humanoid robotics, widening use in construction and agritech, where unstructured settings once resisted automation. Together, these shifts reshape factory economics by curbing reliance on scarce skilled labor and boosting throughput consistency in high-mix lines.

Stringent Quality-Control Mandates Across Regulated Industries

Regulators now view automated optical inspection as essential after repeated recalls exposed limitations of manual checks. EU General Safety Regulation II obliges automakers to embed pedestrian-detection cameras and emergency-braking logic from July 2024, compelling tier-one suppliers to redesign electronic control units around vision models. Pharmaceutical packagers deploy deep-learning vision to verify blister-seal integrity and label accuracy, aligning with FDA validation guidelines for automated inspection. Food processors integrate Cognex In-Sight sensors that achieve 100% foreign-object detection, reducing contamination callbacks and strengthening audit trails.Environmental agencies likewise demand continuous video evidence of effluent compliance, turning vision systems from discretionary spend into risk-mitigation assets that influence procurement decisions.

Complex System-Integration Requirements

Legacy factory lines rely on proprietary field-bus protocols and unshielded wiring that complicate the drop-in replacement of manual inspection with camera systems. Harsh shop-floor vibration and electromagnetic noise degrade image fidelity, demanding ruggedized optics and lengthy calibration cycles. When multi-sensor fusion adds LiDAR or thermal inputs, integrators must synchronize data streams across heterogeneous real-time operating systems, extending deployment timelines for small and mid-sized enterprises that lack in-house expertise. Custom middleware and safety certification inflate project budgets, sometimes eclipsing initial ROI calculations and postponing adoption.

Other drivers and restraints analyzed in the detailed report include:

1. Surge in Automotive ADAS Camera Integration
2. Edge-AI Chipsets Lowering Latency & Power for On-Device Vision
3. Shortage of Skilled Computer-Vision Engineers

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

In 2024 hardware accounted for 68.0% of computer vision market revenue as enterprises purchased industrial cameras, illumination units and dedicated processors to retrofit production lines. Within this total, edge-AI accelerators exhibit a 24.5% CAGR through 2030, the fastest trajectory among all sub-components, as designers replace discrete GPU farms with low-power ASICs and NPUs embedded at the image source. Camera modules remain the largest slice, yet their dollar share narrows as intelligent sensors merge image capture and inference, trimming cabling costs and latency. Optics vendors profit from hyperspectral lenses that detect material signatures beyond the visible spectrum for agriculture and recycling. On the software side, containerized inference stacks and middleware now receive annual subscription budgets larger than perpetual-license algorithms, reflecting the pivot toward continuous model retuning. The computer vision market size for hardware is forecast to exceed USD 34 billion by 2030, supported by resilient capital expenditure among automotive and electronics OEMs.

Software platforms contribute 32.0% of 2024 outlay and grow steadily as firms valorize data pipelines and DevOps integration over one-off deployments. Edge orchestration frameworks help distribute model updates across thousands of endpoints, turning device fleets into adaptive sensor networks. The shift aligns with rising cyber-security concerns that favor on-premises data handling and transparent audit trails. As a result, systems integrators bundle turnkey stacks that compress time-to-value for mid-tier factories lacking dedicated ML teams, in turn expanding addressable demand for the computer vision market.

The Computer Vision Market is Segmented by Components (Hardware and Software), by End-User Industry (Life Science, Manufactur Automotive, Retail and E-Commerce, Logistics and Warehousing and More) and Geography.

Geography Analysis

Asia-Pacific commanded 41.0% of the computer vision market revenue in 2024, buoyed by China's industrial camera sales that rose from CNY 18.5 billion in 2023 to CNY 20.7 billion in 2024, a 28.35% jump tied to rapid robotics adoption. Japan's chip foundries and South Korea's smartphone OEMs sustain high unit demand for wafer-scale AOI tools, while India scales precision-agriculture pilots to offset climate stress on food supply. Government green-factory programs subsidize retrofits with smart cameras, anchoring a steady capital-spending stream even amid macro headwinds. Export-control policies restricting top-tier GPUs push local fabs toward domestic accelerators, gradually lifting regional self-reliance.

The Middle East exhibits the fastest trajectory at 17.2% CAGR to 2030, propelled by Saudi Arabia's USD 100 billion AI fund and the UAE's ambition to rank among the top 10 global AI hubs by 2031. State-backed smart-city builds in Riyadh and Dubai purchase large volumes of surveillance cameras with edge analytics for traffic flow and critical-infrastructure protection. Parallel investments in logistics automation at ports and free zones further enlarge the computer vision market in the Gulf.

North America benefits from NHTSA's impending automatic-braking mandate, driving continuous ADAS camera shipments, while the US Department of Defense bankrolls vision-centric autonomy projects, sustaining a robust procurement c. Europe's Industry 4.0 policy fund supports AI-powered inspection retrofits, and its strict labeling standards stimulate demand in food and pharma plants. However, talent scarcity and chip export curbs moderate near-term growth, highlighting the need for local training initiatives and diversified silicon supply.

1. Intel Corporation
2. Cognex Corporation
3. Keyence Corporation
4. Sony Group Corp.
5. NVIDIA Corporation
6. Omron Corporation
7. Basler AG
8. Teledyne FLIR LLC
9. Qualcomm Inc.
10. Google LLC
11. Advanced Micro Devices (AMD)
12. Adlink Technology Inc.
13. Hikvision Robotics
14. Stemmer Imaging AG
15. Dahua Technology
16. Zebra Technologies
17. Amazon Web Services (AWS)
18. Clarifai Inc.
19. Allied Vision Technologies
20. OpenCV.ai
21. Matrox Imaging

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Rising adoption of vision-guided robotics in manufacturing
  • 4.2.2 Stringent quality-control mandates across regulated industries
  • 4.2.3 Surge in automotive ADAS camera integration
  • 4.2.4 Edge-AI chipsets lowering latency and power for on-device vision
  • 4.2.5 Hyperspectral and neuromorphic sensors opening new use-cases
• 4.3 Market Restraints
  • 4.3.1 Complex system-integration requirements
  • 4.3.2 Shortage of skilled computer-vision engineers
  • 4.3.3 Escalating data-labeling cost inflation
  • 4.3.4 Export-control curbs on advanced vision processors
• 4.4 Value/Supply-Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Porter's Five Forces
  • 4.7.1 Threat of New Entrants
  • 4.7.2 Bargaining Power of Buyers
  • 4.7.3 Bargaining Power of Suppliers
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Components
  • 5.1.1 Hardware
    • 5.1.1.1 Cameras
    • 5.1.1.2 Processors (GPUs / ASIC / FPGA)
    • 5.1.1.3 Optics and Lighting
  • 5.1.2 Software
    • 5.1.2.1 Traditional Algorithms
    • 5.1.2.2 Deep-Learning Frameworks
    • 5.1.2.3 Edge Middleware
• 5.2 By End-user Industry
  • 5.2.1 Life Sciences
  • 5.2.2 Manufacturing
    • 5.2.2.1 Electronics Assembly
    • 5.2.2.2 Food and Beverage
    • 5.2.2.3 Packaging
  • 5.2.3 Defense and Security
  • 5.2.4 Automotive
    • 5.2.4.1 ADAS
    • 5.2.4.2 Autonomous Vehicles
  • 5.2.5 Retail and E-commerce
  • 5.2.6 Logistics and Warehousing
  • 5.2.7 Agriculture and Forestry
  • 5.2.8 Other Industries
• 5.3 By Geography
  • 5.3.1 North America
    • 5.3.1.1 United States
    • 5.3.1.2 Canada
    • 5.3.1.3 Mexico
  • 5.3.2 Europe
    • 5.3.2.1 Germany
    • 5.3.2.2 United Kingdom
    • 5.3.2.3 France
    • 5.3.2.4 Italy
    • 5.3.2.5 Spain
    • 5.3.2.6 Russia
    • 5.3.2.7 Rest of Europe
  • 5.3.3 Asia-Pacific
    • 5.3.3.1 China
    • 5.3.3.2 Japan
    • 5.3.3.3 South Korea
    • 5.3.3.4 India
    • 5.3.3.5 ASEAN
    • 5.3.3.6 Australia and New Zealand
    • 5.3.3.7 Rest of Asia-Pacific
  • 5.3.4 Middle East
    • 5.3.4.1 GCC
    • 5.3.4.2 Turkey
    • 5.3.4.3 Rest of Middle East
  • 5.3.5 Africa
    • 5.3.5.1 South Africa
    • 5.3.5.2 Nigeria
    • 5.3.5.3 Rest of Africa
  • 5.3.6 South America
    • 5.3.6.1 Brazil
    • 5.3.6.2 Argentina
    • 5.3.6.3 Rest of South America

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share Analysis
• 6.4 Company Profiles (includes Global level Overview, Market level overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share for key companies, Products and Services, Recent Developments)
  • 6.4.1 Intel Corporation
  • 6.4.2 Cognex Corporation
  • 6.4.3 Keyence Corporation
  • 6.4.4 Sony Group Corp.
  • 6.4.5 NVIDIA Corporation
  • 6.4.6 Omron Corporation
  • 6.4.7 Basler AG
  • 6.4.8 Teledyne FLIR LLC
  • 6.4.9 Qualcomm Inc.
  • 6.4.10 Google LLC
  • 6.4.11 Advanced Micro Devices (AMD)
  • 6.4.12 Adlink Technology Inc.
  • 6.4.13 Hikvision Robotics
  • 6.4.14 Stemmer Imaging AG
  • 6.4.15 Dahua Technology
  • 6.4.16 Zebra Technologies
  • 6.4.17 Amazon Web Services (AWS)
  • 6.4.18 Clarifai Inc.
  • 6.4.19 Allied Vision Technologies
  • 6.4.20 OpenCV.ai
  • 6.4.21 Matrox Imaging

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-space and Unmet-Need Assessment