搜索资源列表
PE
- 图像识别的文本识别方法-text Image Recognition Recognition
code
- 针对实际项目采用了webservice进行搭建分布应用及多线程进行分布式并行开发应用。本项目主要针对图象学的图象处理对已存在的图象进行数字识别,本项目还利用BP神经网络(人工智能)技术进行识别应用,本项目采用OCR、体征、BP三种识别方法进行有效识别,识别效率达到98 -100 ,运行效率95ms/56ms/0.9ms。-Webservice used for the actual project to build distributed applications and multi-threa
UC3010drv
- parallax adjuster for image recognition under linux
android-ocr-master
- 谢谢您注册,实现图片文字识别,谢谢您注册,实现图片文字识别-Thank you for registering, realize image character recognition, thank you register, realize image character recognition
PY
- python版本网络抢票软件源码,一、运行环境: 基于python2.7 二、原理: 图像识别基于tesseract 数据抓包使用httpwatch, IE,识别出所有的POST请求,获取各步骤中数据,分析页面里token等 三、用法: 修改conf_example.py里的买票信息, 然后运行 -python version of the network software source code to grab votes, a run environment: Based on python
huang
- 车牌图像去噪算法,可以增强车牌图像,让车牌识别的效率更高。-The license plate image denoising algorithms, can enhance the license plate image, make the efficiency of license plate recognition is higher.
Coding-OCR-recognition
- 现有基于机器视觉的智能检测技术是实现其生产质量快速、自动检测与控制的新型重要手段。在此基础上,本文介绍了基于HALCON机器视觉软件的检测系统和针对化妆品瓶底批号的图像处理关键技术,包括灰度值调整、形态学运算、字符分割及识别数字对象-Existing machine vision based intelligent detection technology is to achieve its production quality fast, automatic detection and con
wumi2
- 1.登陆判断更改为Cookies,方便维护 2.增强链接判断识别目前可识别【网络图片(jpg gif png 格式),youku视频,MP3】 3.增加自定义友情链接 4.最新评论和友情链接使用application减少数据库开支 5.增加置顶功能 6.调整提取配置文件为单独文件,方便制作模板和升级维护-1. Change the landing judgment Cookies, easy maintenance 2. Enhance links judgment re
基于噪声点检测的中值滤波方法_马学磊
- 图像识别中,对噪点的检测的中值滤波的方法。(Image recognition, median filtering method for the noise detection)
16182
- 用于图片的查找,二值化,灰度化,车牌的定位,字符的分割,字符的识别。(For image search, two values, gray, license plate positioning, character segmentation, character recognition.)
Chapter8_FaceRecognition
- 人脸识别,图像分割。代码都有,全套人脸识别代码(Face recognition, image segmentation. Code has a full set of face recognition code)
23214419BFA-code
- 实现图像识别,基于小波变换实现图像特征提取,然后神经网络进行训练(The image recognition is realized, the image feature extraction is realized based on wavelet transform, and then the neural network is trained.)