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《Visual C++_MATLAB图像处理与识别实用案例精选》本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章,第1章-第6章是图像处理与识别的基础内容,包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别;第7章-第10章是图像处理与识别的工程实例,涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例,并结合理论算法,提供了大量MATLAB代码程序,以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。
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该程序是利用matlab进行车牌分割步骤中有关车牌字符分割的程序。能很好的实现matlab车牌字符分割。-
The program is the use of matlab for segmentation step plate on license plate character segment of the program. Can be a very good realize matlab license plate character segment.
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基于MATLAB的车牌照自动识别:通过对原始图像进行预处理、车牌子图像的定位与分割、字符的识别,可以较为准确的实现车牌照的字符识别。-MATLAB-based car license plate recognition: the original image is preprocessed by the car brand positioning and image segmentation, character recognition, you can achieve more accurat
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本书系统地介绍了图像处理与识别的基本原理、典型方法和实用技术。全书共分12章,第1章-第6章是图像处理与识别的基础内容,包括图像科学综述、MATLAB语言图像编程、图像增强、图像分割、图像特征提取和图像识别;第7章-第10章是图像处理与识别的工程实例,涵盖了医学图像处理、文字识别和自导引小车路径识别等应用实例,并结合理论算法,提供了大量MATLAB代码程序,以帮助读者掌握如何使用MATLAB语言快速进行算法的仿真、调试和估计等方法。第11章-第12章,是两个综合性较强的实例,分别足Visual
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这是本人的课设的代码与照片,汽车牌照的识别,使用到二值变换,图像字字符分割,及模式识别中的数字识别方法。一种基于MATLAB平台来操作的
-This is my class-based code and photos, vehicle license plate identification, the use of binary transform the character of the image word segmentation, and pattern recognition, n
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The goal of Optical Character Recognition (OCR) is to classify optical patterns (often contained in a digital image) corresponding to alphanumeric or other characters. The process of OCR involves several steps including segmentation, feature extracti
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matlab实现车牌识别,含有字母和数字库方便匹配,分割有效识别准确,可以运行,希望有所助益。-Matlab license plate recognition, contain letters and convenient character matching, segmentation effectively identify accurately, you can run, want to help.
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基于matlab的对易拉罐底字符的定位与辨识,使用了图像滤波,分割,定位,模式匹配等技术-Based on MATLAB the cans at the end of the character of localization and identification, the use of the image filtering, segmentation, orientation, mode matching technology
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用matlab实现车牌试别,包括定位、分割和字符识别,识别方法是神经网络。(Using MATLAB to realize license plate classification, including location, segmentation and character recognition. The recognition method is neural network.)
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