Hand Gesture Detection and Segmentation Based on Difference Background Image with Complex Background

Zhang, Qiuyu; Fan, Chen; Liu, Xinwen

doi:10.1109/icess.2008.23

Cited by 26 publications

(11 citation statements)

References 2 publications

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“…Literatürde el jestinin tespiti konusunda kullanılan algoritmalardan biri ten rengi tespitinin yapılması ve el jestinin belirlenmesidir [31]- [33]. Fakat el jestinin sadece ten rengi ile tespit edilmesi vücudun diğer bölümlerinin el jestiyle karıştırılması ya da ortamda ten rengine yakın renklerdeki objelerin de bulunabilmesi ve bunların el jestinin belirlenmesinde sorunlara neden olmasından dolayı tek başına başarılı bir algoritma değildir.…”

Section: Sonuçlarunclassified

Inverter air conditioner intelligent system design

Taşkıran¹,

Kahraman²,

Yoğun³

2018

Pamukkale J Eng Sci

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Section: Sonuçlarunclassified

Inverter air conditioner intelligent system design

Taşkıran¹,

Kahraman²,

Yoğun³

2018

Pamukkale J Eng Sci

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“…The classic image segmentation algorithm commonly adopted the single threshold background difference method in [7]. Its background was updated only by the weighted average method.…”

Section: The Drawbacks Of the Single Threshold Algorithmmentioning

confidence: 99%

A New Moving Object Detection Approach with Adaptive Double Thresholds

Qiao²,

Zhao

2013

2013 International Conference on Computational and Information Sciences

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In order to improve the rate of vehicle detection, this paper proposed an adaptive double thresholds motion object mask algorithm. This novel method used multiple-frame average algorithm to initialize the background, and dynamically updated two of high and low thresholds by functional link neural network method. Meanwhile, the motion mask algorithm was used to identify the region of foreground and background to update the current background. The foreground object was extracted from dynamic double thresholds background difference method. Then combined with the mathematical morphology, the binary images became much smoother. The experimental results demonstrated that this detecting algorithm was more accurate and robust.

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“…However they have considered constant background behind the signer. Q. Zhang et.al [3] have proposed a hand gesture detection and segmentation system in complex background based on difference background image between consecutive image frames by using 3 principle of normal distribution. But the system fails for video sequences in which background has hand gesture and changes due to adding or removing parts of background.…”

Section: Introductionmentioning

confidence: 99%

A novel hand segmentation method for multiple-hand gesture recognition system under complex background

Choudhury

Talukdar

Sarma

2014

2014 International Conference on Signal Processing and Integrated Networks (SPIN)

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Human Computer Interaction (HCI) has become very important in today's world. Existing HCI techniques like keyboard, mouse, joysticks etc. limit the speed and naturalness of our interaction. Hand gestures provide a more natural way of communicating with the computer. Hand segmentation is the most crucial step in every hand gesture recognition system. All subsequent steps greatly depend on the quality of segmentation. If data is lost due to improper segmentation, it can hardly be recovered in the later stages of gesture recognition process. In this paper, we present a robust and effective method of hand segmentation which overcomes problems such as skin color detection, complex background removal, complexity from multiple gesturers in front of the camera and variable lighting condition.

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Hand Gesture Detection and Segmentation Based on Difference Background Image with Complex Background

Cited by 26 publications

References 2 publications

Inverter air conditioner intelligent system design

Inverter air conditioner intelligent system design

A New Moving Object Detection Approach with Adaptive Double Thresholds

A novel hand segmentation method for multiple-hand gesture recognition system under complex background

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