Handwriting Recognition (HWR) Market is Expected to Reach US$ 3,819.0 Mn By 2025

Handwriting Recognition (HWR) Market is Expected to Reach US$ 3,819.0 Mn By 2025

According to a new market research report published by Credence Research “Handwriting Recognition (HWR) Market (By Type – Online and Offline; By Application: Automotive; Education and Literature; Enterprise and Field Services; Healthcare and Others) - Growth, Future Prospects, Competitive Analysis and Forecast 2017 - 2025”, the global handwriting recognition (HWR) market was valued at US$ 1,039.3 Mn in 2016 and is expected to grow at a CAGR of 15.7% during 2017 to 2025.

The complete report is available at http://www.credenceresearch.com/report/handwriting-recognition-hwr-market

Market Insights:

The handwriting recognition (HWR) market has been majorly driven by increasing applications in the fields of automotive, education, healthcare and various field services. The technology is designed to read handwritten articles/symbols and convert them to machine-readable text. The market growth is primarily governed by the corporate and government enterprises sector. Document management is one of the major concerns across different enterprises. Handwriting recognition helps in effective digital storage of documents, thereby fueling the market penetration. Additionally, growing application of handwriting recognition in automotive infotainment systems is another major factor fueling the market growth. Expanding application area is expected to provide substantial push to the market growth during the forecast period from 2017 to 2025.

The key players of handwriting recognition (HWR) system market include MyScript, Nuance Communications, Inc., SELVAS AI, Inc., Hanwang Technology Co., Ltd., Paragon Software Group, PhatWare Corporation, SinoVoice (Beijing Jietong Huasheng Technology Co. Ltd.), and Sciometrics, LLC.

Table Of Content:

Chapter 1 Preface
1.1 Report Description
1.1.1 Purpose of the Report
1.1.2 Target Audience
1.1.3 USP and Key Offerings
1.2 Research Scope
1.3 Research Methodology
1.3.1 Phase I – Secondary Research
1.3.2 Phase II – Primary Research
1.3.3 Phase III – Expert Panel Review
1.3.4 Assumptions
1.3.5 Approach Adopted

Chapter 2 Executive Summary
2.1 Market Snapshot: Global Handwriting Recognition (HWR) Market
2.2 Global Handwriting Recognition Market, By Type
2.3 Global Handwriting Recognition Market, By Application
2.4 Global Handwriting Recognition Market, By Geography

Chapter 3 Market Dynamics
3.1 Market Overview
3.1.1 Global Handwriting Recognition (HWR) Market Revenue and Growth, 2015 – 2025, (US$ Mn)
3.2 Market Inclination Insights
3.2.1 Growing efforts towards multilingual recognition
3.2.2 Periodic upgrades of handwriting recognition software/apps
3.3 Market Drivers
3.3.1 Continued demand from the corporate enterprises and educational sectors
3.3.2 Growing adoption of handwriting recognition across the automotive industry
3.4 Challenges ...

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The handwriting recognition (HWR) market is segmented, based on type, into following categories

  • Online Handwriting Recognition
  • Offline Handwriting Recognition

On the basis of type, the global handwriting recognition (HWR) market was led by the online segment in 2016. Online handwriting recognition (HWR) refers to the real-time conversion of text being written on a PFA, special digitizer or tablets, among others. The online HWR technique makes use of sensors wherein such sensors capture numerous features such as pen-tip movement and strokes over the touch screen surface. The segment accounted for more than half of the overall HWR market across the world in 2016.

Offline handwriting recognition (HWR) refers to the conversion of text from an image into digital letter codes which can be further used in text-processing and computer applications. This method is largely used in enterprises and government offices where text from numerous predefined forms needs to be extracted for recording digitally. However, factors such as largely varying writing styles, handwritings and limitations in language recognition have resulted in limited applications of the offline method for handwriting recognition.

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