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SYSTEM AND METHOD FOR IMAGE IDENTIFIER BASED ON SINGULAR VALUE DECOMPOSITION AND FEATURE POINT

机译:基于奇异值分解和特征点的图像识别系统及方法

摘要

A system and a method for comparing SVD(Singular Value Decomposition)-based images are provided to search and recognize a still image easily and quickly which has been illegally changed due to copying or intentional attack or a still image whose original characteristics have been changed. A feature extracting module(110) extracts one or more features of an inputted still image by using strength of Gaussian curvature of each pixel from the still image. An identifier detecting module(120) detects a local identifier based on an SVD with respect to a neighbor block of the extracted features. A matching module(20) discriminates whether a still image has been duplicated by comparing the detected local identifier and a still image identifier database(30) storing one or more still images, The feature extracting module extracts the features by using a Y component of the inputted still image, reduces differentiated noise of the Y component, and extracts the features by measuring strength of the Guassian curvature by using an eigen value of a Hessain matrix.
机译:提供一种用于比较基于SVD(奇异值分解)的图像的系统和方法,以容易且快速地搜索和识别由于复制或故意攻击而非法改变的静止图像或原始特性已改变的静止图像。特征提取模块(110)通过使用来自静止图像的每个像素的高斯曲率的强度来提取输入的静止图像的一个或多个特征。标识符检测模块(120)基于关于所提取特征的相邻块的SVD来检测本地标识符。匹配模块(20)通过将检测到的本地标识符与存储一个或多个静止图像的静止图像标识符数据库(30)进行比较来识别是否已经复制了静止图像。特征提取模块通过使用图像的Y分量来提取特征。输入静止图像,减少Y分量的微分噪声,并通过使用Hessain矩阵的特征值测量高斯曲率的强度来提取特征。

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