Air-writing Recognition of Farsi Digits based on Depth Image

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MALEKI REZA; Mohamadi Shahram

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Journal: IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY Year:2018 | Volume:10 | Issue:35-36 Page(s): 43-56

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Title

Air-writing Recognition of Farsi Digits based on Depth Image

Author(s)

MALEKI REZA | Mohamadi Shahram | Issue Writer Certificate

Keywords

Kineckt sensorQ1

Depth imageQ1

slope variation detectionQ1

Hidden Markov ModelQ2

Abstract

Recognition of hand writing on paper, on display or on air is an important challenge in computer vision. Air-writing recocognition is especially difficult due to three dimentionality of space. In this research work the aim is recognizing persian digits which are written in air in front of a Kineckt sensor using a fingertip and the sensor can detect the digit using its Depth image. For hand and fingertip segmentation we use K-means algorithm. To extract the features we use a novel method called slope variation detection, and to classify the features Hidden Markov Models (HMM) is used. Recognition rate of Persian digits using a local database with 10 times mutual validation is 96%. This novel method was compared with some other similar methods in the literature. The results confirm relative priority of the proposed method.

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APA: Copy

MALEKI, REZA, & Mohamadi, Shahram. (2018). Air-writing Recognition of Farsi Digits based on Depth Image. IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY, 10(35-36 ), 43-56. SID. https://sid.ir/paper/370385/en

Vancouver: Copy

MALEKI REZA, Mohamadi Shahram. Air-writing Recognition of Farsi Digits based on Depth Image. IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY[Internet]. 2018;10(35-36 ):43-56. Available from: https://sid.ir/paper/370385/en

IEEE: Copy

REZA MALEKI, and Shahram Mohamadi, “Air-writing Recognition of Farsi Digits based on Depth Image,” IRANIAN COMMUNICATION AND INFORMATION TECHNOLOGY, vol. 10, no. 35-36 , pp. 43–56, 2018, [Online]. Available: https://sid.ir/paper/370385/en

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