含噪文本图像的中英文文种识别研究

从文本图像中提取局部特征来进行文字种类识别,对图像的质量要求较高,而提取文本图像的整体特征进行识别,则能够克服了这个问题.分析中、英文文本图像的纹理特征,通过Gabor滤波器分析提取全局特征,再用支持向量机的方法进行文种分类识别.实验结果表明,该方法可以很好地区分含噪文本图像中的中文和英文.     

Understanding NFC-Net: a deep learning approach to word-level handwritten Indic script recognition

Neural Computing and Applications - This paper presents a deep learning architecture modified for resource-constrained environments, called Non-Fully-Connected Network or NFC-Net, based on...     

Efficient zone identification approach for the recognition of online handwritten Gurmukhi script

Neural Computing and Applications - In this paper, a real-time recognition approach for online handwritten Gurmukhi character combinations with matras (Gurmukhi Vowels) has been addressed....     

An ultra-specific image dataset for automated insect identification

Automated identification of insects is a tough task where many challenges like data limitation, imbalanced data count, and background noise needs to be overcome for better performance. This paper describes such an image dataset which consists of a limited, imbalanced number of images regarding six genera of subfamily Cicindelinae (tiger beetles) of order Coleoptera. The diversity of image collection is at a high level as the images were taken from different sources, angles and on different scales. Thus, the salient regions of the images have a large variation. Therefore, one of the main intentions in this process was to get an idea about the image dataset while comparing different unique patterns and features in images. The dataset was evaluated on different classification algorithms including deep learning models based on different approaches to provide a benchmark. The dynamic nature of the dataset poses a challenge to the image classification algorithms. However transfer learning models using softmax classifier performed well on the current dataset. The tiger beetle classification can be challenging even to a trained human eye, therefore, this dataset opens a new avenue for the classification algorithms to develop, to identify features which human eyes have not identified.

     

基于广义Hough变换的手写汉字文档关键词提取

提出了一种基于广义Hough变换的手写汉字文档关键词提取技术.对于待提取的手写文档图像,采用字符像素逐点匹配和投票的方式进行广义Hough变换,在参数空间中定位出手写关键词图像的位置.本技术对传统的广义Hough变换进行了修改,突破了形状匹配需要完整轮廓信息的局限,简化了局部特征的计算,对手写汉字文档图像中具有局部形变、部分旋转和缩放的手写关键词能够有效提取.对于提取的相同关键词建立训练集,用签名识别的方法对书写者建模,能够达到书写者身份鉴别的目的.     

文档图像二值化算法VFCM

为了提高基于拍摄方式的文档图像的二值化效果,降低光学字符识别(optical character recognition,OCR)系统的文字识别错误率,提出了一种全局阈值与局部阈值相结合的二值化算法-VFCM.该算法使用最大方差比方法产生全局阈值,使用FCM(Fuzzy C-Means)聚类方法产生局部阈值.这两种方法的结合能够较好地保留字符的笔画细节,并能有效地消除伪影.实验结果表明,该算法可以取得比较好的二值化效果,并能带来OCR系统识别率的有效提高.     

电子公章在公文流转中的软件方案

介绍如何实现B/S结构下的办公自动化系统中的电子公章技术,通过对BMP图像数据位的分析读写配合公文流转的特点以及MD5加密算法,实现用户对电子公文的加盖公章操作,并提供一种相对安全的电子公文签署方案.采用ASP语言及SQL Server 2000数据库进行举例,介绍如何具体实现BMP图像的电子公章.     

A voting-based technique for word spotting in handwritten document images

Multimedia Tools and Applications - Word spotting in handwritten document images is a field of immense interest due to its widespread applications. Recognition-free and recognition-based approaches...     

IDEA: A new dataset for image aesthetic scoring

Multimedia Tools and Applications - The aesthetic quality assessment of image is a challenging work in computer vision field. The recent research work used the deep convolutional neural network to...     

基于身份的电子公文数字签名方案

随着信息技术的发展和电子政务的深入实施,公文的电子文件形式代替了传统的纸质文件形式,这种变化不可避免地引起了电子公文传输过程中的安全性问题。从辫群上求根问题困难的角度出发,提出了一种基于身份的电子公文数字签名方案,说明了攻击者能够伪造此签名仅当他能够求解辫群上的求根问题,分析结果表明该方案是有效和可行的。