求翻译,汉译英,紧急啊!

求翻译,汉译英,紧急啊!
一个车牌识别系统可分为三个步骤：车牌检测,字符分割和字符识别.车牌检测主要会受到倾斜、光照、污染等的影响,算法实现较复杂.近年来提出了许多车牌检测算法,但是它们大多有着不足,无法在复杂环境下很好地实现车牌的实时识别.边缘检测算法随拍摄影响变化,当没有清晰车牌边缘时无法成功检测出车牌.颜色和纹理综合特征检测算法准确率较好,但是受光照影响十分明显,且算法复杂度高,效果不行.对于形态学车牌检测算法,它容易受类车牌字符的影响,检测速度比较慢.以上这些检测算法拥有的缺点都是因为算法缺少了适应能力.本文提出了Boosting算法中的代表AdaBoost算法,这是一种构造准确分类器的自适应学习算法,它通过结合多个特征来构造精确分类器,最终完成车牌的检测.
本文研究了车牌识别中关键的技术,详细介绍了车牌定位、字符分割、特征提取和字符识别的方法,并且对车牌定位与基于AdaBoost算法的车牌识别进行了研究,结果表明AdaBoost算法明显提高了车牌检测的稳定性和精度性.
这些是作为论文摘要的翻译,希望翻译的规整点,望高人指导,谢谢啊.
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翻得不行,请高人手工翻译.

A license plate recognition system can be divided into three steps: license plate detection, character segmentation and character recognition. License plate detection will be inclined, light, pollution and so on, algorithm complexity. In recent years, put forward a lot of license plate detection algorithm, but most of them are inadequate, not in a complex environment, achieve a good license plate recognition. Edge detection algorithm with filming the impact of changes, when there is no clear license plate edge can be detected in the plate. Combination of color and texture feature detection accuracy is better, but by the influence of illumination is very obvious, and the algorithm complexity is high, no effect. The morphology of license plate detection algorithm, it is easy to be affected by class of license plate character effects, detection speed is slow. These detection algorithm has shortcomings because of lack of adaptation algorithm. This paper presents the Boosting algorithm in the AdaBoost algorithm, this is a kind of structure accurately classifier adaptive learning algorithm, it combines many features to construct accurate classifier, finally complete license plate detection.This paper studies the key technologies in license plate recognition, license plate location, introduces in detail the character segmentation, feature extraction and recognition method of license plate location, and with the AdaBoost algorithm based on license plate recognition is discussed, the results show that the AdaBoost algorithm can evidently improve the stability and precision of license plate detection of.