三维物体空间取向归一化的一种新方法

本文提出三维物体空间取向归一化的新方法，该方法从理论上分析了用主轴方法归一化三维物体空间取向时主轴的唯一性确定问题，本文提出了基于３Ｄ矩的主轴唯一性判别准则解决了由主轴多义性给三维物空间取向归一化带来的困难，我们的方法突破了现有方法只允许物体小角度空间取向变化或者形心必须在物体表面以内的限制条件，基于３Ｄ矩的主轴唯一性判别准则使主轴取向的计算更加稳定，可靠，实验结果表明，对各种取向的物体，利用本文     

Digit recognition in a natural scene with skew and slant normalization

This paper proposes a method to recognize digits in a natural scene, such as telephone numbers on a signboard. Candidate regions of digits are extracted from an image through contrast enhancement, edge extraction, and labeling. Since the target text patterns are in a 3D space, unlike traditional character recognition problems, we have to deal with the image transformation effect due to the orientation in the 3D space and projection. We have to cancel the effect as much as possible before digit recognition. In our method, the image transformation effect is modeled as skew and slant. In the proposed method, simplified Hough transform is used for the skew normalization. After the skew normalization, the remaining effect of image transformation is corrected by circumscribing digit patterns with tilted rectangles and affine transformation. In experiments, we tested a total of 1,332 images of signboards with 11,939 digits. We obtained a digit extraction rate of 99.2% and a correct digit recognition rate of 98.8%.Received: 15 December 2003, Accepted: 21 October 2004, Published online: 2 February 2005     

DC-Hunter:一种基于字节码匹配的危险智能合约检测方案

近年来，智能合约中的漏洞检测任务已受到越来越多的关注。然而，缺少源代码和完备的检测特征限制了检测的效果。在本文中，我们提出了DC-Hunter：一种基于字节码匹配的智能合约漏洞检测方案。它可以通过已知的漏洞合约找到类似的漏洞合约，并且可以直接应用于现实世界中的智能合约，无需源码和预先定义的漏洞特征。为了让提出的方法更加切实可行，我们应用程序切片来降低无关代码的影响，通过规范化减少编译器版本带来的差异，并使用图嵌入算法来捕捉函数的结构信息，从而显著减少误报和漏报。此外，借助DC-Hunter我们揭露了一种新型的危险合约。我们发现有一些合约是伪漏洞合约，专门用于诱骗他人尝试进行攻击，从而窃取攻击者的以太币，这种合约称为"蜜罐合约"。我们实现了DC-Hunter的原型，并将其应用于现实世界的智能合约，共有183份危险的合约被报出并确认，其中包括160份漏洞合约和23份蜜罐合约。     

On-line recognition (OLREC): A novel approach to visual pattern recognition

A pattern recognition system has been developed which is capable of recognizing high contrast two-dimensional visual patterns and which is insensitive to the translation, rotation and size of a pattern. The unique characteristics of the system are its speed, its low cost and the fact that it is completely self-contained.

A new technique for image recognition, suitable for applications such as industrial robotics, is presented. The technique provides invariance to rotation, translation and magnification of the image. An intelligent camera system is used to input an image, to center it, to normalize it with respect to size and to convert it into polar coordinate form. The image is then integrated over r and θ to provide two orthogonal profiles. The input profiles are compared to the reference images using a threshold comparison technique designed to provide a simple hardware implementation. Rotation of the image is handled by a one-dimensional shifting of the radial profile.

Seven experiments were performed to test the system. The results of these experiments are discussed and possible improvements to the system are suggested.     

Automated microscopy system for mosaic acquisition and processing

An automatic mosaic acquisition and processing system for a multiphoton microscope is described for imaging large expanses of biological specimens at or near the resolution limit of light microscopy. In a mosaic, a larger image is created from a series of smaller images individually acquired systematically across a specimen. Mosaics allow wide‐field views of biological specimens to be acquired without sacrificing resolution, providing detailed views of biological specimens within context. The system is composed of a fast‐scanning, multiphoton, confocal microscope fitted with a motorized, high‐precision stage and custom‐developed software programs for automatic image acquisition, image normalization, image alignment and stitching. Our current capabilities allow us to acquire data sets comprised of thousands to tens of thousands of individual images per mosaic. The large number of individual images involved in creating a single mosaic necessitated software development to automate both the mosaic acquisition and processing steps. In this report, we describe the methods and challenges involved in the routine creation of very large scale mosaics from brain tissue labelled with multiple fluorescent probes.     

γ射线剂量率的线性化数字显示方法

计数管测量的Υ射线脉冲计数率与剂量率成非线性关系。本文利用分段线性近似和斜率归一化的方法求数字显示剂量率.方法简单、直观、线性误差小。     

基于分离度的图象特征提取与识别方法

对于图象中不同类别（以其统计分布函数一表征）的可识别性，分离度的统计定义可做出定量的描述。根据分离度在一一对应映射变换下的不变性，应用Ｋａｒｈｕｎｅｎ－Ｌｏｅｖｅ变换对两类分布撮识别特征，发现分离度只依赖于特征值最大和最小的两个特征向量。而且，分离度的大小依赖于特征值怀某个定定值的偏差。由此我们提出一个识别模型，使每次分类后的样本集的特征值都趋近于两上定值，从而得到最佳的识别效果。由该模型设计的     

光照鲁棒的人脸识别

传统的人脸识别方法对待识别人脸图像的质量要求较高,而且要求所采集的人脸图像的光照情况与人脸训练库的光照情况的差异不能太大,这就限制了人脸识别系统运行的环境条件,从而限制了人脸识别的应用。为了降低人脸识别对环境条件的要求,真服光照对人脸识别的影响。本文分析了人脸图像的幅频特性和相频特性,提出了频域光照归一化的人脸识别方法,使得对任何光照条件下采集的图像经过归一化后,光照情况与训练库中的图像完全相同,同时保留了人脸的可区分性。因为人脸之间差异的信息量一般较少,故本文运用最小非零特征向量作为人脸特征,通过实验仿真,与传统方法相比本文人脸识别方法对光照变化具有鲁棒性。