HSI空间和改进 C-means的彩色人民币号码分割方法

针对采集到的人民币号码图像都是彩色图像并携带有噪声这一现象,本文提出基于 HSI空间和改进的 C-means算法的人民币彩色号码图像分割方法。选用 HSI颜色空间作为彩色分割空间,在 HSI空间内,将 HSI的 3-D搜索问题转化为 3个 1-D的搜索问题,求取图像在 3个 1-D方向上的灰度直方图,该方法根据图像当前点 3×3邻域内每个像素灰度值与当前点灰度值差值的大小情况,确定聚类算法中当前点的灰度值 p(m)的值,采用 C-means聚类算法分别确定文字和非文字的聚类中心,利用欧式距离进行人民币号码前景和背景的聚类判断。该方法直接对彩色人民币号码图像进行分割,考虑了当前点与邻域像素点之间的相互关系,具有一定的自适应性。实验结果表明,提出的号码图像分割方法不受图像噪声和局部边缘变化的影响,且变换后数据量减少,易于计算,该方法对字母和数字的分割都有效,鲁棒性较强。     

一种基于mean shift的多通道图像分割算法

目的针对目标与背景对象的色彩值比较接近的RGB图像中,目标对象难以有效分割的问题,探索一种基于mean shift的RGB多通道图像的分割方法。方法根据RGB图像的3个通道对颜色的敏感性差异,运用均值偏移算法对RGB图像的3个通道分层聚类,再引入可靠性因子,分别对3个单通道的各聚类像素进行可靠性计算,并保留可靠性高的像素作为分割结果,最后采用逻辑"或"运算融合单通道的分割结果,得到最终分割图像。结果与一般分割算法相比,该方法的分割效果好,误分率低,改善了图像的分割质量。结论该算法具有很好的推广性,能够应用于彩色印品缺陷检测、彩色包装图像检测中。     

一种Lab空间的色域边界描述算法

基于区域分割法,提出一种Lab空间的色域边界描述算法,以更精确地实现图像颜色映射到打印机色域。在Lab空间内,首先用色域边界描述(GBD)对打印机色域进行整体分割描述,然后根据图像每个像素点的色相角计算打印机的线性色域边界(LGB),最后比较图像每个像素点的L值与LGB矩阵L值区间的关系,确定像素点是否在打印机色域边界内。算法在GBD对打印机色域边界进行分割后,还面向图像每个像素点确定打印机的LGB边界,色域边界描述更加精确。实验仿真结果表明,该方法能够更精确、直观地实现图像颜色映射到打印机颜色。     

基于无序分割投影策略与重力模型的图像加密算法

目的解决当前图像算法因其像素置乱和扩散操作与明文无关,导致其抗明文攻击能力较弱,且其置乱过程存在周期性,使其安全性不佳等问题。方法提出基于无序分割投影策略与重力模型的图像加密算法。首先对输入明文进行无序分割,获取重叠子块,并构建每个子块的位置坐标计算模型,输出图像子块的位置;根据明文像素量计算Kent映射的初值,通过迭代Kent映射获取随机序列组;定义位置置乱机制,对重叠子块进行混淆;再引入分割投影策略,互换每个置乱子块中的像素位置,再对其重组,输出置乱密文;通过设计像素质量变化函数替换重力模型的固定质量,改进重力模型,对置乱密文完成像素加密。结果实验结果显示与当前图像加密技术相比,文中算法具有更高的安全性,输出密文中的相邻两像素间的关联度最低,具有更强的抗明文攻击与剪切攻击性能。结论所提加密算法能够较好地用于图像信息安全传输,具有较好的应用价值。     

Color‐edge detection based on discrimination of noticeable color contrasts

Color‐edge detection is an important research task in the field of image processing. Efficient and accurate edge detection will lead to higher performance of subsequent image processing techniques, including image segmentation, object‐based image coding, and image retrieval. To improve the performance of color‐edge detection while considering that human eyes are ultimate receiver of color images, the perceptually insignificant edges should avoid being over‐detected. In this article, a color‐edge detection scheme based on the perceptual color contrast is proposed. The perceptual color contrast is defined as the visible color difference across an edge in the CIE‐Lab color space. A perceptual metric for measuring the visible color difference of a target color pixel is defined by utilizing the associated perceptually indistinguishable region. The perceptually indistinguishable region for each color pixel in the CIE‐Lab color space is estimated by the design of an experiment that considers the local property due to local changes in luminance. Simulation results show that the perceptual color contrast is effectively defined and the color edges in color images are detected while most of the perceptually insignificant edges are successfully suppressed through the proposed color‐edge detection scheme. © 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 332–339, 2009     

采用模糊判别的自适应多窗口立体匹配

考虑到立体匹配过程中存在的不确定性和模糊性,将已经获得广泛应用的模糊理论引入立体匹配领域,使用与人类感知相似的模糊逻辑为基础的HVS彩色图像点颜色相似性测度,然后把这种模糊颜色相似性测度应用到区域匹配方法的多窗口选择和自适应窗口尺寸缩减当中,最后用SSD方法实现了彩色图像的立体匹配.实验结果表明,该方法具有更高的匹配精确性.     

Text binarization in color documents

This article presents a new method for the binarization of color document images. Initially, the colors of the document image are reduced to a small number using a new color reduction technique. Specifically, this technique estimates the dominant colors and then assigns the original image colors to them in order that the background and text components to become uniform. Each dominant color defines a color plane in which the connected components (CCs) are extracted. Next, in each color plane a CC filtering procedure is applied which is followed by a grouping procedure. At the end of this stage, blocks of CCs are constructed which are next redefined by obtaining the direction of connection (DOC) property for each CC. Using the DOC property, the blocks of CCs are classified as text or nontext. The identified text blocks are binarized properly using suitable binarization techniques, considering the rest of the pixels as background. The final result is a binary image which contains always black characters in white background independently of the original colors of each text block. The proposed document binarization approach can also be used for binarization of noisy color (or gray‐scale) document images. Several experiments that confirm the effectiveness of the proposed technique are presented. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 262–274, 2006     

海洋遥感彩色图像中的海洋数据读取技术

基于对海洋遥感彩色图像的像素点数据矩阵的理解,提出了一种基于MATLAB软件的海洋遥感数据读取技术.依据这项技术,用户可以从卫星遥感获取的各种海洋要素彩色图像中读取对应于各个像素点的海洋要素数据.在MATLAB软件中,图像是由像素点构成的,全部图像信息均以矩阵的形式存储和运算.一幅图像可能包含一个数据矩阵和一个颜色映射表矩阵.用户可使用MATLAB软件读入图像,并通过所读取图像中包含的数据矩阵和颜色映射表矩阵,将图像区域中的像素点的颜色与色标中的颜色进行比较来获得像素点所表示的海洋要素数据.以一幅东中国海海域的海表面温度(SST)彩色图像实例说明了如何应用该技术来提高遥感彩色图像信息的读取能力.     

基于颜色传递和对比度增强的夜视图像彩色融合

针对基于颜色传递夜视图像彩色融合算法存在的热目标不突出问题,提出一种基于颜色传递和对比度增强的彩色融合算法。该算法首先利用非线性扩散和迭代阈值分割方法提取出图像中的热目标,然后在HSI颜色空间利用热目标和灰度融合图像对颜色传递得到的初步彩色融合图像进行调整,接着将处理结果变换回RGB颜色空间,得到最终的融合图像。实验结果表明,利用该算法得到的融合图像不仅与人眼视觉感知习惯一致,而且显著增强了目标与背景的对比度,从而有效提高了目标的可探测性。     

基于自适应前景分割及粒子滤波的人体运动跟踪

提出了在图像序列中用自适应前景分割及粒子滤波对人体的3-D运动轨迹进行跟踪的方法．首先建立了像素点的高斯模型,并结合图像帧间的差分信息以及灰度分布的先验概率等因素完成了图像中人体的自适应分割．根据所得到的分割结果建立了透视投影下的运动平面跟踪模型．根据投影过程的非线性以及图像中噪声分布的未知性,提出了粒子滤波的跟踪方法,并最终得到了人体运动平面的3-D轨迹．实际人体运动图像序列的实验证明,本文方法能有效地跟踪人体运动的3-D轨迹,并反映出在此跟踪问题上粒子滤波比传统的扩展卡尔曼滤波更具优势．     

Mango Leaf Disease Identification Using Fully Resolution Convolutional Network

Due to the high demand for mango and being the king of all fruits, it is the need of the hour to curb its diseases to fetch high returns. Automatic leaf disease segmentation and identification are still a challenge due to variations in symptoms. Accurate segmentation of the disease is the key prerequisite for any computer-aided system to recognize the diseases, i.e., Anthracnose, apical-necrosis, etc., of a mango plant leaf. To solve this issue, we proposed a CNN based Fully-convolutional-network (FrCNnet) model for the segmentation of the diseased part of the mango leaf. The proposed FrCNnet directly learns the features of each pixel of the input data after applying some preprocessing techniques. We evaluated the proposed FrCNnet on the real-time dataset provided by the mango research institute, Multan, Pakistan. To evaluate the proposed model results, we compared the segmentation performance with the available state-of-the-art models, i.e., Vgg16, Vgg-19, and Unet. Furthermore, the proposed model's segmentation accuracy is 99.2% with a false negative rate (FNR) of 0.8%, which is much higher than the other models. We have concluded that by using a FrCNnet, the input image could learn better features that are more prominent and much specific, resulting in an improved and better segmentation performance and diseases’ identification. Accordingly, an automated approach helps pathologists and mango growers detect and identify those diseases.     

Fuzzy clustering and Whale-based neural network to food recognition and calorie estimation for daily dietary assessment

The calorie value of the food items taken by the person in everyday life needs to be monitored to reduce the risk of obesity, heart problems, and diabetes, etc. The calorie estimator in the existing models has reduced accuracy since the calorie value of each food varies with mass. This paper introduces a dietary assessment system based on the proposed Cauchy, Generalized T-Student, and Wavelet kernel based Wu-and-Li Index Fuzzy clustering (CSW-WLIFC) based segmentation and the proposed Whale Levenberg Marquardt Neural Network (WLM-NN) classifier. The proposed CSW-WLIFC based segmentation segments the image based on the existing WLI-FC algorithm. A novel CSW based kernel function is utilized in the segmentation process. Feature vectors such as color, shape, and texture are extracted from the segmented image. The Neural Network is trained with the Whale-Levenberg Marquardt (WLM) model to recognize each food item from the tray image. The proposed calorie estimator calculates the calorie value of each food item. From the simulation results, it is evident that the proposed model has the improved performance than the existing models with the values of 0.999, 0.9643, 0.9627, and 0.0184 for the segmentation accuracy, macro average accuracy, standard accuracy, mean square error, respectively.     

用于彩色图像分割的改进遗传FCM算法

本文提出了一种适用于彩色图像分割的遗传模糊C均值聚类(GAFCM)算法.该算法使用Ohta等人提出的彩色特征集中的第一个分量作为图像像素的一维特征向量,并利用由像素空间到特征空间的映射来改进目标函数,从而大大降低了运算量;使用对特征空间结构没有特殊要求的特征距离代替欧氏距离,从而克服了特征空间结构对聚类结果的影响;使用引入FCM优化的遗传算法来搜索最优解,从而提高了搜索速度.实验表明,该算法不但能很好地分割彩色图像,而且具有运算量小、收敛速度快的优点.     

基于方差和显著性特征的超声图像分割方法研究

针对超声图像对比度小导致的影像上相邻灰度差别很小,人眼有时难于区分的问题,提出了一种基于方差和显著性特征的超声图像分割方法。首先提取图像中已知样本像素点的方差和显著性特征;然后利用支持向量机根据提取的样本像素点方差和显著性特征进行样本训练,得到分类模型;最后根据训练模型对整幅图像上的像素点进行分类,实现图像的有效分割。实验结果表明该方法针对超声图像的分割是有效的。     

Color constancy through inverse-intensity chromaticity space

Existing color constancy methods cannot handle both uniformly colored surfaces and highly textured surfaces in a single integrated framework. Statistics-based methods require many surface colors and become error prone when there are only a few surface colors. In contrast, dichromatic-based methods can successfully handle uniformly colored surfaces but cannot be applied to highly textured surfaces, since they require precise color segmentation. We present a single integrated method to estimate illumination chromaticity from single-colored and multicolored surfaces. Unlike existing dichromatic-based methods, the proposed method requires only rough highlight regions without segmenting the colors inside them. We show that, by analyzing highlights, a direct correlation between illumination chromaticity and image chromaticity can be obtained. This correlation is clearly described in "inverse-intensity chromaticity space," a novel two-dimensional space that we introduce. In addition, when Hough transform and histogram analysis is utilized in this space, illumination chromaticity can be estimated robustly, even for a highly textured surface.     

A novel automatic color transfer algorithm between images

Abstracts

A color transfer algorithm between images intends to modify the colors in the source image by borrowing the color characteristics from the target image. In this paper, we present a novel automatic color transfer algorithm between images. This algorithm is able to proceed on color transfer with no user intervention, and produce visually plausible resultant images. To the best of our knowledge, our algorithm is the first to achieve this kind of automation. Our technique consists of an image segmentation algorithm, a swatch merging algorithm, and a pattern recognition algorithm. The image segmentation algorithm generates a number of swatches with different features in the source and target images. The swatch merging algorithm merges a particular swatch with its neighbors in the source image when it fails to pass the normality test. The pattern recognition algorithm then automatically matches these swatches for color transfer. We develop a boundary transition algorithm to make possible a consistent transition between two boundaries of patches. Experimental results demonstrate that, without any user intervention, our technique performs color transfer results with good visual realism. The technique is superior to the original user‐intervention color transfer algorithm.     

基于DeepLabv3+的图像语义分割优化方法

目的为了实现良好的图像语义分割精度,同时尽可能降低网络的参数量,加快网络训练速度,提出基于DeepLabv3+的图像语义分割优化方法。方法编码器主干网络增加注意力机制模块,并采用更密集的特征池化模块有效聚合多尺度特征,同时使用深度可分离卷积降低网络计算复杂度。结果基于CamVid数据集的对比实验显示,优化后网络的MIoU分数达到了71.03%,在像素精度、平均像素精度等其他方面的评价指标上较原网络有小幅提升,并且网络参数量降低了12%。在Cityscapes的测试数据集上的MIoU分数为75.1%。结论实验结果表明,优化后的网络能够有效提取图像特征信息,提高语义分割精度,同时降低模型复杂度。文中网络使用城市道路场景数据集进行测试,可以为今后的无人驾驶技术的应用提供参考,具有一定的实际意义。     

中国木版年画的画版处理技术研究

为了对中国木板年画进行数字化保护,本文以套色印刷的朱仙镇木板年画为例,采用图像处理技术从年画中提取出线版和色版.处理流程分为前处理、线版提取、色版提取和后处理四个部分.以像素的RGB和CMY颜色分量比率计算灰度值,将图中大部分彩色转化为白色,依此对年画进行去色处理;再经过阈值处理、形态学处理和线条光滑获得年画的黑色线版.主要利用K-均值聚类方法获取年画的色版.本文的处理结果很好地表现了年画的画版原貌,所提出的处理框架对于中国木板年画的数字化保护具有较高的实用价值.     

High-Movement Human Segmentation in Video Using Adaptive N-Frames Ensemble

A wide range of camera apps and online video conferencing services support the feature of changing the background in real-time for aesthetic, privacy, and security reasons. Numerous studies show that the Deep-Learning (DL) is a suitable option for human segmentation, and the ensemble of multiple DL-based segmentation models can improve the segmentation result. However, these approaches are not as effective when directly applied to the image segmentation in a video. This paper proposes an Adaptive N-Frames Ensemble (AFE) approach for high-movement human segmentation in a video using an ensemble of multiple DL models. In contrast to an ensemble, which executes multiple DL models simultaneously for every single video frame, the proposed AFE approach executes only a single DL model upon a current video frame. It combines the segmentation outputs of previous frames for the final segmentation output when the frame difference is less than a particular threshold. Our method employs the idea of the N-Frames Ensemble (NFE) method, which uses the ensemble of the image segmentation of a current video frame and previous video frames. However, NFE is not suitable for the segmentation of fast-moving objects in a video nor a video with low frame rates. The proposed AFE approach addresses the limitations of the NFE method. Our experiment uses three human segmentation models, namely Fully Convolutional Network (FCN), DeepLabv3, and Mediapipe. We evaluated our approach using 1711 videos of the TikTok50f dataset with a single-person view. The TikTok50f dataset is a reconstructed version of the publicly available TikTok dataset by cropping, resizing and dividing it into videos having 50 frames each. This paper compares the proposed AFE with single models and the Two-Models Ensemble, as well as the NFE models. The experiment results show that the proposed AFE is suitable for low-movement as well as high-movement human segmentation in a video.     

一种足球机器人色标识别方法

以足球机器人视觉系统为研究对象,提出了一套基于颜色信息的色标识别方法。在假设颜色样本图像中存在唯一主色的条件下,提出了排异聚类主色提取算法,该算法适合足球机器人视觉系统的色标颜色提取过程,具有抑制噪声和保持主要颜色信息的能力。基于颜色相似系数判定图像中待识别像素颜色与样本颜色之间的相似性。采用网格搜索方法实现色标的搜索过程。通过形态学滤波方法对色标预分割结果进行后处理。实验结果表明,该方法具有较理想的彩色色标识别效果。