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一维条形码打印系统
- 条形码的生成原理： 条形码的第一数据部分是由 7个数字形成的，其形成的方法详述如下： n 首先使用 产生和 匹配的字母码，该字母码有6个字母组成，字母限于A和B。产生字母码的列表如下 字母码 0 AAA 1 AABABB 2 AABBAB 3 AABBBA 4 ABAABB 5 ABBAAB 6 ABBBAA 7 ABABAB 8 ABABBA 9 ABBABA 表一 映射表 n 将 和 产生的字母码按位进行搭配，来产
Thinned
- java开发的二值图像细化算法程序，能够从二值图像中提取图像骨架-java development of the binary image thinning algorithm procedures, from the binary image extracted image skeleton
Digit_Recomodule
- This an digit recognition application. (OCR or ICR application). First you draw a digit in the picturebox. Then the image processing begins and recognize the digit and returns you the result. I used correlation matching algorithm for character recogn
car(c)
- 车牌识别系统c++源代码，VS 2005开发,包括灰度处理、均衡化、边缘提取、二值化等功能-c license plate recognition system source code, VS 2005 developers, including Gray, balance, edge extraction, Binary function
lbp_matlab
- 局部二进制模式ＬＢＰ，介绍了三种不同的ＬＢＰ算子，用于分析图像的局部纹理特征．-local binary mode LBP, introduced three different LBP operator, Image Analysis for the local texture characteristics.
Corner
- 一种比较好用的边缘检测方法CORNER Find corners in tensity image. ％ CORNER works by the following step: ％ 1. Apply the Canny edge detector to the gray level image and obtain a ％ binary edge-map. ％ 2. Extract the edge contours from the edge-map, fill the ga
matlabtocarrecognition
- 车牌识别matlab源程序 基于颜色的车牌定位和分割技术研究与实现 function [seg] = character_segmentation(bw) ％ character_segmentation: Returns the digit segments in the supplied binary image. ％ The function uses the \"segment\" function, keeping only the seven ％ s
houghcircle
- 利用hough变换来进行圆形检测.Function uses Standard Hough Transform to detect circles in a binary image.According to the Hough Transform for circles, each pixel in image space corresponds to a circle in Hough space and vise versa. upper left corner of image is t
binary+chars24X48
- 汽车车牌识别中，字符识别是用的字符和数字模板，binary+chars24X48，大小是24*48
Program_Model
- 本程序为图象二值化，以及对图象马赛克，基于人体肤色划分等，功能齐全-procedures for the two binary images, and the right image mosaics, based on the delineation of human color, multifunctional
车牌定位
- 车牌定位 使用时打开此例题目录下pic中的图片，然后依次单击按钮“转”、“1”、“2”、“3”、“4”和“5”，就可以实现精确的车牌定位。 具体步骤 1.24位真彩色->256色灰度图。 2.预处理:中值滤波。 3.二值化:用一个初始阈值T对图像A进行二值化得到二值化图像B。 初始阈值T的确定方法是:选择阈值T=Gmax-(Gmax-Gmin)/3,Gmax和Gmin分别是最高、最低灰度值。 该阈值对不同牌照有一定的适应性,能够保证背景基本被置为0,以突出牌照区域。 4.削弱背景干扰。对图
c第二章 matlab语言基础h2
- 用Canny算子检测图像的边缘 P0404：图像的阈值分割 P0405：用水线阈值法分割图像 P0406：对矩阵进行四叉树分解 P0407：将图像分为文字和非文字的两个类别 P0408：形态学梯度检测二值图像的边缘 P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象-with Canny operator to detect the edges in the image P0404 : image thresholding segmentation P0405 : water
Tesseract-OCR 源代码，文字识别
- Tesseract-OCR 源代码，文字识别，支持中文-The Tesseract OCR engine was one of the top 3 engines in the 1995 UNLV Accuracy test. Between 1995 and 2006 it had little work done on it, but it is probably one of the most accurate open source OCR engines available. The
xcvx.rar
- 通过二值分割等一系列图像编程对车牌进行定位校正。仅供参考,Through a series of binary segmentation image programming on the license plate positioning correction. For reference only
seismic-segy-write
- 三维地震数据文件的写入程序，改程序直接用于写入二进制数据-Three-dimensional seismic data file writing procedure, change the program used to write binary data directly
USPS.rar
- 用于手写体数字识别的USPS样本数据库和将MAT格式的样本数据库转换成二值化图像并以行程编码存储,For handwritten numeral recognition of the USPS database and a sample format of samples MAT database into binary image and the Run-Length Coding storage
Gaborwaveletandlocalbinarypatternswithagoodalgorit
- Gabor小波和局部二值模式结合的一种人脸识别算法 不错的算法-Gabor wavelet and local binary patterns with a good algorithm for face recognition algorithm
lbp
- local binary patterns用来描述图像纹理的一个算子-local binary patterns used to describe the texture of an operator
local-binary-pattens
- LBP人脸识别：基于对小波分解和局部二进制模式(LBP)分析，提出了一种多级LBP直方图的序列特征(M—HSLBP)的提取方法。-LBP Face Recognition: Based on the wavelet decomposition and local binary pattern (LBP) analysis, a multi-stage sequence of LBP histogram features (M-HSLBP) extraction method.
[16---2011]---local-binary-LDA-for-FaceR
- Extracting discriminatory features from images is a crucial task for biometric recognition. For this reason, we have developed a new method for the extraction of features from images that we have called local binary linear discriminant analysis (LB