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Method of and apparatus for segmenting foreground and background information for optical character recognition of labels employing single layer recurrent neural network

机译:利用单层递归神经网络分割前景和背景信息以识别标签的光学字符的方法和装置

摘要

A method and apparatus for processing a greyscale input of an image, particularly of a shipping label, into a binary output image in which foreground information is segmented from the background information and contrasts between adjacent regions having different background densities are obliterated is described. A neuron employing a 5×5 input neighborhood having a unique neuron activation function is shown. No explicit line process is employed. Output is biased toward a particular one of the output values by employing non-linear feedback as a function of both the grey scale value for the pixel corresponding to the label site being updated and the most recent value of the label site. The otherwise strong contribution from a gradient term in the energy function is suppressed by a shunting inhibition when the shunting inhibition function detects that the pixel lies on or near a boundary between adjacent regions of differing background intensities.
机译:描述了一种用于将图像,特别是运输标签的灰度输入处理为二进制输出图像的方法和设备,其中从背景信息中分割出前景信息,并且消除了具有不同背景密度的相邻区域之间的对比度。示出了采用具有独特神经元激活功能的5×5输入邻域的神经元。没有采用显式的行处理。通过采用非线性反馈,将输出偏向输出值中的特定一个,该非线性反馈是与要更新的标签位点相对应的像素的灰度值和标签位点的最新值两者的函数。当分流抑制功能检测到像素位于背景强度不同的相邻区域之间的边界上或附近时,分流抑制会抑制能量函数中梯度项的其他强烈贡献。

著录项

  • 公开/公告号US5710830A

    专利类型

  • 公开/公告日1998-01-20

    原文格式PDF

  • 申请/专利权人 UNITED PARCEL SERVICE;

    申请/专利号US19950574254

  • 发明设计人 LEE F. HOLEVA;

    申请日1995-11-30

  • 分类号H04N1/40;

  • 国家 US

  • 入库时间 2022-08-22 02:40:19

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