数字识别是多年来的研究热点，也是字符识别中的一个特别重要的问题。因为阿

数字识别是多年来的研究热点，也是字符识别中的一个特别重要的问题。因为阿拉伯数字全世界通用，并且数字的识别和处理也常常是一些自动化系统的核心和关键,手写体数字识别研究通用性强,且意义重大。此系统通过对手写体数字图像进行二值化和反色处理，在已经定位的数字区域上进行特征提取，采用模板匹配法对手写体数字进行识别。最后用Visual C++ 6.0进行了实现,可以较准确的识别手写体数字。

結果 (英文) 1:

Digital identification is a hotspot for many years, is a particularly important issue for character recognition. Because the Arabic numerals common worldwide, as well as digital identification and treatment are often some of the automation system of core and key, high universality of handwritten numeral recognition, and meaningful. Through this system for handwritten numeral image binarization and invert the colors, has been positioned on the range of numbers for feature extraction, using template matching on handwritten digit recognition. Finally Visual c 6.0 has been achieved, more accurate recognition of handwritten digits.

結果 (英文) 2:

Digital Identification research focus over the years, but also character recognition a particularly important issue. Because Universal digits worldwide, and digital identification and treatment are often some of the core and key automation systems, digital handwriting recognition research versatility, and significant. Through this system of handwritten digital image binarization and anti-color processing, has been positioned in the digital area for feature extraction, using the template matching method for handwritten digit recognition. Finally, Visual C + + 6.0 has been achieved, can be more accurate identification of handwritten numbers.

結果 (英文) 3:

Numeral recognition is a hotspot of study for years, also is the character recognition of a particularly important issue. Because the Arabia digital common throughout the world, and the recognition and processing of digital often is the core and key of some automation system, handwritten numeral recognition research is universal, and significant. This system is based on the handwritten digital image is two value and color processing, feature extraction in digital region has orientation, recognition of handwritten digits using template matching method. Finally, using Visual C 6 to achieve, can be identified accurately handwritten numerals.