资源列表
traffic_warning_zip
- Traffic Warning Sign Recognition Matlab Code For Code understanding and Flow of program visit blob analysis, detection, gui, image processing, recognition, recognition and detection, sign recognition, signal processing, traffic warning sign recogniti
car_reader
- 文图车辆牌照识别SDK开发包，含文字说明-provide car lience sdk, include introduction
MulCSharp(DLL)
- C#实现车牌识别功能 应用于智能交通领域 对于全天候各类图片拥有极好的鲁棒性和识别率-C# license plate recognition in the field of intelligent transportation has excellent robustness and recognition rate for the weather all kinds of pictures
Asprise-OCR-CSharp-Windows_Vista_64bit-4.0
- Asprise-OCR-CSharp-Windows_Vista_64bit-4.0
photosearch
- matlab实现的简单的图像检索，通过收集图像的信息，在图像集合中找到与目标相似的图像-matlab to achieve a simple image retrieval, image collection, image collection to find images similar objectives
SIFT-all
- 基于SIFT的 匹配算法。设计众多内容，内容比较详细 值得参考-SIFT-based matching algorithm. The content more detail worth considering
MulVB(DLL)
- Vb实现车牌识别功能 应用于智能交通领域 对于全天候各类图片拥有极好的鲁棒性和识别率-Vb license plate recognition has excellent robustness and recognition rate for the weather all kinds of pictures used in the field of intelligent transportation
Images embalance
- 图像相似度计算，利用hog特征，不变矩，包含canny因子计算 来计算两张图片的相似度。可以用来进行图片检索-Image similarity calculation, hog characteristics, invariant moments contain a canny factor to calculate the similarity of two images. Can be used for image retrieval
ShapeContext
- 形状上下文的matlab源码，执行demo1.m和demo2.m两个文件可以查看效果-Shape context
wjy
- hough变换检测圆 并且描绘半径和圆心坐标 效果不错-Hough transform to detect circle effect is good
imgUi
- 通过Tesseract的识别包，编写了一个UI，可以直接选择图片识别，增加的是最新版本的学习库，提供的完全可以运行的工程，环境是eclipse+jdk1.5.06,已包含jar包-Package through Tesseract recognition, writing a UI, you can directly select a picture identification, the increase is the latest version of the learning librar
AGAST-corner-detector
- 多尺度快速角点检测算法（FAST).Adaptive and generic corner detection based on the accelerated segment test. Computer Vision–ECCV 2010-Multi-scale fast corner detection algorithm (FAST) Adaptive and generic corner detection based on the accelerated segment test