资源列表
gait_recognition__a_challenging_signal_processing_
- 一篇关于步态识别的综述，希望对大家有用，pdf格式-An overview of gait recognition, we want to be useful, pdf format
LPR_VISL
- LPR車牌辨識軟體,是由VISL實驗室開發的demo source code,可以直接在Matlab環境下執行(demo),程式主要使用類神經網路演算法(Neural Network)-License Plate Recognition-- Matlab source code, it s from VISL please visit website: http://visl.technion.ac.il/ for more information
HomeRobotVisionsystem
- 机器人双目识别系统，一个简单的例子，对于开发双目系统的人可做参考。-Binocular recognition system, a simple example, for the development of human binocular system.
subpixel
- 基于多尺度小波特征的高光谱影像亚像素目标识别、基于灰度矩的CCD图像亚像素边缘检测算法研究、基于矩的亚像素边缘检测算法的对比研究等-Based on multi-scale wavelet feature in Hyperspectral subpixel target identification, Gray moment CCD image sub-pixel edge detection algorithm, based on the moment of sub-pixel edge de
licenseplaterecognition
- license plate recognition
PhysicsLicensePlates
- license plates of India
LicensePlateRecognitionproductsandtechnology
- license plate localization.
segmentationbyabbas
- The major problem with machine printed Arabic character segmentation is the shape of the letter depending on its location in the word. In this paper, a new machine printed Arabic character segmentation algorithm, which is based on the vertical hi
RecognitionofOffLineHandwrittenArabicWordsUsingHi
- Hidden Markov Models (HMM) have been used with some success in recognizing printed Arabic words. In this paper, a complete scheme for totally unconstrained Arabic handwritten word recognition based on a Model discriminant HMM is presented. A
RecognitionofOflinePrintedArabicText
- This paper describes a technique for automatic recognition of off-line printed Arabic text using Hidden Markov Models. In this work different sizes of overlapping and non-overlapping hierarchical windows are used to generate 16 features from each ver
FindEyes1.1
- 视频处理方面；对于人脸的识别，简单的一个程序。-Video processing for face recognition, a simple procedure.
Charactorshibie
- 用Gabor函数实现的字符识别程序 适合初学者仔细研读 细心体会-Gabor function is implemented using character recognition program for beginners carefully read carefully Experience