二元微分联合变换相关器实现图像识别的研究

为了克服二元联合变换相关器的取阈和实时性问题,采用微分运算与二元联合变换相关器结合的方法.联合功率谱中,由于干扰项随频率的变化率比需要的信息量随频率的变化率慢得多,因此可以采用微分方式削弱干扰项,增强互相关信号,对微分后的功率谱再进行二值化非线性处理得到优化功率谱,然后对优化功率谱进行傅里叶逆变换,得到目标和图像的相关输出.模拟实验结果表明,所提出的相关器能很好地抑制自相关峰,增强互相关峰,具有更强的鲁棒性.而且该方法在处理过程中,不需选择阈值,简单的微分及二值化操作使之具有更强的实时性.     

应用相移技术的形态学联合变换相关器

用数学形态学的方法对相关器的输入图像进行预处理,有效的去除图像噪声和提取边缘;采用相移技术在光学频谱面去除零衍射级,并对其进行二值化。计算机仿真结果表明,本文提出的联合变换相关技术增强了相关器的抗噪声性能,锐化了相关峰强度,提高了衍射效率和对目标的识别能力。     

基于谱二值化及复制技术的光电混合高效联合变换相关器

提出一种将联合变换功率谱二值化处理并进行复制以提高联合变换相关器性能的方法，对该方法给出了理论分析并导出了谱复制时应满足的条件，证明在该条件下不仅可以提高光效率，而且可同时大大提高相关峰极值强度，相关峰锐度及信噪比。     

基于群体智能边缘提取算法的联合变换相关器

为提取联合变换相关器输入面图像的边缘,改善相关器的识别效果,提出了一种基于群体智能的图像特征提取方法,并将其应用于联合变换相关器的输入面图像预处理中.实验结果表明该算法有效提取了图像的边缘,锐化了相关峰,提高了联合变换相关器的目标识别能力.群体智能计算机并行算法与联合变换相关器光学并行系统相结合,为实现实时高效的光电混合目标识别系统奠定了坚实的理论基础.     

灰度梯度自适应阈值二值化算法的FPGA实现

根据红外图像中目标与背景之间灰度比梯度特性,提出了一种自适应阈值二值化算法,并利用FPGA并行流水处理特点,采用模块化设计,完成了该算法的FPGA实现.算法实现由灰度比二值化模块和自适应阈值T模块两部分组成.灰度比二值化模块根据同步信号流水计算模板内灰度比梯度,并根据差值大小进行二值化.自适应阈值T模块根据背景的变化规律实时调整输出阈值大小,以实现对灰度比二值化模块作用范围的控制.实验结果表明,该算法虚警率较低,运算耗时少,满足实时处理的要求.     

光学子波变换（3）：应用

本文综述了子波变换的发展概况，总结了光学子波变换的一些应用领域，重点论述了在纹理分割中的应用，提出了联合子波变换相关器及其应用于二值图象的特征提取，给出了多通道盖伯变换在纹分割中的应用设想以及初步的研究结果。     

基于模糊逻辑的抗畸变光学模式识别

将多值击中击不中变换（ＭＶＨＭＴ）引入用于二值图像识别的联合变换相关器（ＪＴＣ）。ＭＶＨＭＴ对形态学击中击不中变换（ＨＭＴ）的性能进行了改善,基于模糊的概念,引入不确定点的定义,使得容易受到畸变干扰的点对判别结果的作用降低,从而在不损失图像信息的前提下,具有输入图像和参考模板之间进行精确匹配的能力,同时还提高了目标识别的抗畸变能力。利用新颖的多值互补编码方法,通过ＪＴＣ一步实现ＭＶＨＭＴ,相关后的图像通过取高阈值的分割方法来实现对目标的准确判断。     

基于小波多尺度综合的低对比度目标识别

光电混合联合变换相关器能够对目标进行自动探测识别和跟踪。为使联合变换相关器对低对比度目标进行有效探测与识别,提出了一种基于小波多尺度综合的边缘提取新方法,对输入图像进行预处理。计算机模拟实验和光学实验证明,该方法使相关器在输入图像对比度低、信噪比较低时仍然能够产生较强的相关峰输出,扩展了光电混合联合变换相关器的应用范围。     

一种新的二值化方法在车牌检测中的应用

车牌定位过程中二值化方法的选择尤为重要,何时二值化以及选取何种二值化方法对检测结果的影响明显。考虑到车牌区域有着丰富的边缘信息,车牌区域的亮度以及区域标准差,能给二值化阈值提供有价值参考信息,文中根据车牌的特征提出了一种新的自适应二值化算法,并采用区域融合及连通域计算方法提取车牌。实验证明,此二值化算法对图像灰度变化、...     

基于DSP实时联合变换相关器系统设计

实时性问题是联合变换相关器能否在实际中得到应用所必须解决的关键性问题之一.设计了一种基于DSP的实时联合变换相关器系统,实现了系统的控制和识别,解决了二维快速反傅立叶变换.实验结果表明系统的运行速度得到来了极大的提高.     

An algorithm for fast adaptive image binarization with applications in radiotherapy imaging

Locally adaptive image binarization with a sliding-window threshold can be an effective tool for various image processing tasks. We have used the method for the detection of bone ridges in radiotherapy portal images. However, a straight-forward implementation of sliding-window processing is too time consuming for routine use. Therefore, we have developed a new thresholding criterion suitable for incremental update within the sliding window, and we show that our algorithm gives better results on difficult portal images than various publicly available adaptive thresholding routines. For small windows, the routine is also faster than an adaptive implementation of the Otsu algorithm that uses interpolation between fixed tiles, and the resulting images are equally good.     

Adaptive–interpolative binarization with stroke preservation for restoration of faint characters in degraded documents

A novel technique for binarization with stroke preservation of faint characters in degraded documents is proposed. It works in a multi-scale framework with an adaptive–interpolative thresholding technique. Instead of computing a global threshold value, it computes the local threshold values for a small set of grid points by observing the intensity pattern of the pixels lying in the concerned grid cells. Estimated thresholds are used, in turn, to compute the threshold values of all the remaining pixels using a fast-yet-efficient interpolation procedure. To handle noises in degraded images, this grid-based adaptive thresholding is applied in successively reducing scales to obtain the near-optimal binarization as a set of connected components. After a post-processing meant for stroke preservation with these connected components, we get the final output. Exhaustive experimentation and comparison with other existing methods have been successfully carried out with benchmark datasets and also with our own datasets.     

一种改进的退化文本图像二值化方法

文本图像二值化是文本图像识别的重要步骤,由于光照不均或文档水渍等原因导致文本图像退化,增加了文本图像识别的难度。本文对一种局部阈值算法进行了改进,首先对图像进行水平投影,根据直方图的极小点对版面进行简单划分,再利用全局阈值法估算出更为准确的各区域字符笔画宽度,从而自适应地得到适当的窗口尺寸,再利用对比图和局部阈值进行图像二值化,并结合OTSU图像消除原算法产生的伪轮廓。实验与分析表明,改进后的方法能够明显消除因笔画粗细不均、字符大小不同而产生的前景像素误识问题。     

击中与否单通道光学处理器用于人脸识别

根据击中击不中运算的定义提出基于光学单通道相关器的灰度腐蚀的概念,证明了图像对具有三个灰度级的结构核的腐蚀操作等价于击中击不中形态学操作;给出选择正确的结构核灰度级的条件;设计了只有一个图像和一个灰度结构核的单通道非相干光学相关器来并行一步取阈完成击中与否运算。最后给出该处理器用于人脸识别的实验结果。     

GMM Based Adaptive Thresholding for Uneven Lighting Image Binarization

Journal of Signal Processing Systems - Image binarization of uneven lighted images, using thresholding techniques, is still a challenging task. Adaptive thresholding methods are the widely adopted...     

Binarization of color document images via luminance and saturationcolor features

This paper presents a novel binarization algorithm for color document images. Conventional thresholding methods do not produce satisfactory binarization results for documents with close or mixed foreground colors and background colors. Initially, statistical image features are extracted from the luminance distribution. Then, a decision-tree based binarization method is proposed, which selects various color features to binarize color document images. First, if the document image colors are concentrated within a limited range, saturation is employed. Second, if the image foreground colors are significant, luminance is adopted. Third, if the image background colors are concentrated within a limited range, luminance is also applied. Fourth, if the total number of pixels with low luminance (less than 60) is limited, saturation is applied; else both luminance and saturation are employed. Our experiments include 519 color images, most of which are uniform invoice and name-card document images. The proposed binarization method generates better results than other available methods in shape and connected-component measurements. Also, the binarization method obtains higher recognition accuracy in a commercial OCR system than other comparable methods.     

Iterative cross section sequence graph for handwritten character segmentation.

The iterative cross section sequence graph (ICSSG) is an algorithm for handwritten character segmentation. It expands the cross section sequence graph concept by applying it iteratively at equally spaced thresholds. The iterative thresholding reduces the effect of information loss associated with image binarization. ICSSG preserves the characters' skeletal structure by preventing the interference of pixels that causes flooding of adjacent characters' segments. Improving the structural quality of the characters' skeleton facilitates better feature extraction and classification, which improves the overall performance of optical character recognition (OCR). Experimental results showed significant improvements in OCR recognition rates compared to other well-established segmentation algorithms.