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    • 22. 发明申请
    • EMPLOYING PIXEL DENSITY TO DETECT A SPAM IMAGE
    • 使用像素密度来检测垃圾邮件图像
    • US20110078269A1
    • 2011-03-31
    • US12963514
    • 2010-12-08
    • Ke WEIHao ZhengJay Pujara
    • Ke WEIHao ZhengJay Pujara
    • G06F15/16G06K9/00
    • G06T7/44H04L51/12
    • A network device and method are directed towards detecting and blocking image spam within a message by performing statistical analysis on differences in edge pixel distribution patterns. An image spam detection component receives a message with an image attachment. Physical characteristics of the image are examined to determine whether the image is a candidate for further analysis. If so, then the image may be converted to a grayscale image, and then performing edge detection, followed by the elimination of non-maxima and thresholding of weak edges. Edge pixels and then employed to determine a normalized pixel density distribution (PDD). Various statistical analyses are applied to the resulting normalized PDD to determine a likelihood that the image is spam. A signature based exemption may be applied to images improperly identified as spam, based on trusted user feedback.
    • 网络设备和方法旨在通过对边缘像素分布模式的差异进行统计分析来检测和阻止消息内的图像垃圾邮件。 图像垃圾邮件检测组件接收具有图像附件的消息。 检查图像的物理特性以确定图像是否是进一步分析的候选者。 如果是这样,则可以将图像转换成灰度图像,然后执行边缘检测,然后消除弱边缘的非最大值和阈值。 边缘像素,然后用于确定归一化像素密度分布(PDD)。 对所得到的归一化PDD应用各种统计分析以确定图像是垃圾邮件的可能性。 基于信任的用户反馈,基于签名的豁免可能会应用于不正确识别为垃圾邮件的映像。
    • 23. 发明授权
    • Employing pixel density to detect a spam image
    • 使用像素密度来检测垃圾邮件图像
    • US07882177B2
    • 2011-02-01
    • US11834529
    • 2007-08-06
    • Ke WeiHao ZhengJay Pujara
    • Ke WeiHao ZhengJay Pujara
    • G06K9/60
    • G06T7/44H04L51/12
    • A network device and method are directed towards detecting and blocking image spam within a message by performing statistical analysis on differences in edge pixel distribution patterns. An image spam detection component receives a message with an image attachment. Physical characteristics of the image are examined to determine whether the image is a candidate for further analysis. If so, then the image may be converted to a grayscale image, and then performing edge detection, followed by the elimination of non-maxima and thresholding of weak edges. Edge pixels and then employed to determine a normalized pixel density distribution (PDD). Various statistical analyses are applied to the resulting normalized PDD to determine a likelihood that the image is spam. A signature based exemption may be applied to images improperly identified as spam, based on trusted user feedback.
    • 网络设备和方法旨在通过对边缘像素分布模式的差异进行统计分析来检测和阻止消息内的图像垃圾邮件。 图像垃圾邮件检测组件接收具有图像附件的消息。 检查图像的物理特性以确定图像是否是进一步分析的候选者。 如果是这样,则可以将图像转换成灰度图像,然后执行边缘检测,然后消除弱边缘的非最大值和阈值。 边缘像素,然后用于确定归一化像素密度分布(PDD)。 对所得到的归一化PDD应用各种统计分析以确定图像是垃圾邮件的可能性。 基于信任的用户反馈,基于签名的豁免可能会应用于不正确识别为垃圾邮件的映像。
    • 25. 发明申请
    • Automated solicited message detection
    • 自动请求消息检测
    • US20060031346A1
    • 2006-02-09
    • US11080258
    • 2005-03-14
    • Hao ZhengBruce ChuAnirban KunduMiles LibbeyDavid NakayamaJing Zhu
    • Hao ZhengBruce ChuAnirban KunduMiles LibbeyDavid NakayamaJing Zhu
    • G06F15/16
    • G06Q10/107H04L51/12
    • The invention relates to determining electronic text communication distributed in bulk is likely solicited. In one step, a first electronic and a second electronic submission are received. It is determined that the first electronic submission is likely solicited. A first portion is extracted from the first electronic submission and a second portion from the second electronic submission. The content of the first electronic submission influences extraction of the first portion, and the content of the second electronic submission influences extraction of the second portion. A first code is determined for the first portion and a second code is determined for the second portion, where the first code is indicative of the first portion and the second code is indicative of the second portion. The first code is compared to the second code. It is determined that the second electronic submission is likely solicited, at least in part, in response to comparing the first code to the second code.
    • 本发明涉及确定批量散布的电子文本通信可能被请求。 一步,接收第一个电子和第二个电子提交。 确定可能要求第一次电子提交。 从第一电子提交中提取第一部分,并从第二电子提交中提取第二部分。 第一电子提交的内容影响第一部分的提取,并且第二电子提交的内容影响第二部分的提取。 为第一部分确定第一代码,并且为第二部分确定第二代码,其中第一代码指示第一部分,而第二代码指示第二部分。 第一个代码与第二个代码进行比较。 确定可以至少部分地响应于将第一代码与第二代码进行比较来请求第二电子提交。
    • 27. 发明授权
    • Employing pixel density to detect a spam image
    • 使用像素密度来检测垃圾邮件图像
    • US08301719B2
    • 2012-10-30
    • US12963514
    • 2010-12-08
    • Ke WeiHao ZhengJay Pujara
    • Ke WeiHao ZhengJay Pujara
    • G06F15/16G06K9/00
    • G06T7/44H04L51/12
    • A network device and method are directed towards detecting and blocking image spam within a message by performing statistical analysis on differences in edge pixel distribution patterns. An image spam detection component receives a message with an image attachment. Physical characteristics of the image are examined to determine whether the image is a candidate for further analysis. If so, then the image may be converted to a grayscale image, and then performing edge detection, followed by the elimination of non-maxima and thresholding of weak edges. Edge pixels and then employed to determine a normalized pixel density distribution (PDD). Various statistical analyses are applied to the resulting normalized PDD to determine a likelihood that the image is spam. A signature based exemption may be applied to images improperly identified as spam, based on trusted user feedback.
    • 网络设备和方法旨在通过对边缘像素分布模式的差异进行统计分析来检测和阻止消息内的图像垃圾邮件。 图像垃圾邮件检测组件接收具有图像附件的消息。 检查图像的物理特性以确定图像是否是进一步分析的候选者。 如果是这样,则可以将图像转换成灰度图像,然后执行边缘检测,然后消除弱边缘的非最大值和阈值。 边缘像素,然后用于确定归一化像素密度分布(PDD)。 对所得到的归一化PDD应用各种统计分析以确定图像是垃圾邮件的可能性。 基于信任的用户反馈,基于签名的豁免可能会应用于不正确识别为垃圾邮件的映像。
    • 29. 发明申请
    • EMPLOYING PIXEL DENSITY TO DETECT A SPAM IMAGE
    • 使用像素密度来检测垃圾邮件图像
    • US20090043853A1
    • 2009-02-12
    • US11834529
    • 2007-08-06
    • Ke WeiHao ZhengJay Pujara
    • Ke WeiHao ZhengJay Pujara
    • G06F15/16
    • G06T7/44H04L51/12
    • A network device and method are directed towards detecting and blocking image spam within a message by performing statistical analysis on differences in edge pixel distribution patterns. An image spam detection component receives a message with an image attachment. Physical characteristics of the image are examined to determine whether the image is a candidate for further analysis. If so, then the image may be converted to a grayscale image, and then performing edge detection, followed by the elimination of non-maxima and thresholding of weak edges. Edge pixels and then employed to determine a normalized pixel density distribution (PDD). Various statistical analyses are applied to the resulting normalized PDD to determine a likelihood that the image is spam. A signature based exemption may be applied to images improperly identified as spam, based on trusted user feedback.
    • 网络设备和方法旨在通过对边缘像素分布模式的差异进行统计分析来检测和阻止消息内的图像垃圾邮件。 图像垃圾邮件检测组件接收具有图像附件的消息。 检查图像的物理特性以确定图像是否是进一步分析的候选者。 如果是这样,则可以将图像转换成灰度图像,然后执行边缘检测,然后消除弱边缘的非最大值和阈值。 边缘像素,然后用于确定归一化像素密度分布(PDD)。 对所得到的归一化PDD应用各种统计分析以确定图像是垃圾邮件的可能性。 基于信任的用户反馈,基于签名的豁免可能会应用于不正确识别为垃圾邮件的映像。