Offline Signature Verification based on Edge Histogram using Support Vector Machine

Sunil Kumar Dyavaranahalli Sannappa, K. Kiran, Sudheesh Kannur Vasudeva Rao, Y. Jagadeesh
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引用次数: 0

Abstract

Investigation on verification of offline signature has explored a huge sort of techniques on more than one signature datasets, which can be amassed beneath managed conditions. However, these records will not necessarily reflect the characteristics of the signatures in some useful use cases. In this work, introduced a novel feature representation technique called edge histogram and 4 directional histograms for offline signature verification system. For classification of signature support vector machine (SVM) technique employed. Edge is a curve or point where the intensity of an image changes rapidly. Edges represent the boundary of object of an image. Edge detection is a process of detecting edges of an image. Several algorithms are available to detect edges effectively from an image. Canny, Roberts, Prewitt and Sobel are several popular available edge detectors.
基于边缘直方图的支持向量机离线签名验证
对离线签名验证的研究探索了一种基于多个签名数据集的大量技术,这些数据集可以在管理条件下积累。然而,在一些有用的用例中,这些记录不一定反映签名的特征。本文介绍了一种新的特征表示技术——边缘直方图和4个方向直方图,用于离线签名验证系统。对签名进行分类采用支持向量机(SVM)技术。边缘是图像强度快速变化的曲线或点。边缘表示图像中物体的边界。边缘检测是一种检测图像边缘的过程。有几种算法可以有效地从图像中检测边缘。Canny, Roberts, Prewitt和Sobel是几种常用的边缘检测器。
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