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A New Algorithmic Approach for Fingers Detection and Identification

机译:一种新的手指检测与识别算法

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Gesture recognition is concerned with the goal of interpreting human gestures through mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Hand gesture detection in a real time environment, where the time and memory are important issues, is a critical operation. Hand gesture recognition largely depends on the accurate detection of the fingers. This paper presents a new algorithmic approach to detect and identify fingers of human hand. The proposed algorithm does not depend upon the prior knowledge of the scene. It detects the active fingers and Metacarpophalangeal (MCP) of the inactive fingers from an already detected hand. Dynamic thresholding technique and connected component labeling scheme are employed for background elimination and hand detection respectively. Algorithm proposed a new approach for finger identification in real time environment keeping the memory and time constraint as low as possible.
机译:手势识别与通过数学算法解释人类手势的目标有关。手势可以源自任何身体运动或状态,但通常源自面部或手部。在时间和内存是重要问题的实时环境中,手势检测是一项至关重要的操作。手势识别在很大程度上取决于手指的准确检测。本文提出了一种新的算法方法来检测和识别人手的手指。所提出的算法不依赖于场景的先验知识。它从已经检测到的手中检测活动手指和不活动手指的掌指(MCP)。分别采用动态阈值技术和连接组件标记方案进行背景消除和手部检测。该算法提出了一种新的实时环境下的手指识别方法,该方法可以使内存和时间约束尽可能地低。

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