Scale-space color blob and ridge detection

Feature detection in color images frequently consists in image conversion from color to grayscale and then one of grayscale detectors application. This approach has a few disadvantages: some features become indistinguishable in grayscale and features ordering based on response of grayscale detector do not accord with features order of importance from human’s perception point of view. There are two essential contributions in this paper. First, the method for direct detection of blobs and ridges in color images is proposed. Second, for scale-space ridge detection we introduce a 3D non maxima suppression procedure (in two orthogonal directions) which makes ridge detection simple and easy programmable in contrast to Lindeberg’s automatic scale selection approach. The proposed algorithms also produce estimates of blobs sizes and ridges width.     

基于颜色编码和图像隐写术的可逆灰度方法

针对现有方法存在合成灰度图像视觉质量欠佳、重建彩色图像还原度不足的问题,提出一种基于颜色编码和图像隐写术的可逆灰度方法。其利用可逆神经网络构建更高效的颜色编解码器,并引入密集卷积块和通道注意力机制进一步提升网络模型的性能,综合减少编解码过程中的颜色信息丢失。之后,为使灰度图像负载编码信息以及减小嵌入过程导致的图像失真,设计了一种基于修改方向的图像隐写算法,通过自适应权值参数选择,以接近最优的方式满足不同的嵌入容量需求,减少对灰度图像的修改。在Kodak和McMaster数据集上的实验表明,与现有代表性可逆灰度方法相比较,该方法能够生成质量更高的可逆灰度图像以及重建更加还原的彩色图像,在图像可视化时具有更好的视觉效果,在标准参考图像的相似性评价指标方面也取得了更优的性能。     

Perceptual Evaluation of Color‐to‐Grayscale Image Conversions

Color images often have to be converted to grayscale for reproduction, artistic purposes, or for subsequent processing. Methods performing the conversion of color images to grayscale aim to retain as much information about the original color image as possible, while simultaneously producing perceptually plausible grayscale results. Recently, many methods of conversion have been proposed, but their performance has not yet been assessed. Therefore, the strengths and weaknesses of color‐to‐grayscale conversions are not known. In this paper, we present the results of two subjective experiments in which a total of 24 color images were converted to grayscale using seven state‐of‐the‐art conversions and evaluated by 119 human subjects using a paired comparison paradigm. We surveyed nearly 20000 human responses and used them to evaluate the accuracy and preference of the color‐to‐grayscale conversions. To the best of our knowledge, the study presented in this paper is the first perceptual evaluation of color‐to‐grayscale conversions. Besides exposing the strengths and weaknesses of the researched methods, the aim of the study is to attain a deeper understanding of the examined field, which can accelerate the progress of color‐to‐grayscale conversion.     

Interactive two-scale color-to-gray

Current color-to-gray methods compute the grayscale results by preserving the discriminability among individual pixels. However, human perception tends to firstly group the perceptually similar elements while looking at an image, according to the Gestalt principles. In this paper, we propose a novel two-scale approach for converting color images to grayscale. First, we decompose the input image into multiple soft segments where each segment represents a perceptual group of content. Second, we determine the grayscale of each perceptual group via a global mapping by solving a quadratic optimization. Last, the local details are added into the final result. Our approach is efficient and provides users quick feedback on adjusting the prominent gray tones of the results. As an important aspect of algorithm, our approach offers users an easy, intuitive interactive tool for creating art-like black-and-white images from input color images. Experimental results show that our approach better preserves the overall perception and local details. User studies have been conducted to show the applicability of our approach.     

A new steganographic method for color and grayscale image hiding

In this paper, we present a steganographic method for embedding a color or a grayscale image in a true color image. Three types of secret images can be carried by the proposed method: hiding a color secret image, hiding a palette-based 256-color secret image, and hiding a grayscale image in a true color image. Secret data are protected by the conventional crypto system DES. We compare the image quality and hiding capacity of the proposed method with those of the scheme in Lin et al.’s scheme. According to the experimental results, the image quality of the proposed method is better than that of the Lin et al.’s scheme. In addition, annotation data can be hidden with the secret image in the host image. The hiding capacity of the proposed method is greater than that of other compared schemes. The experimental results show that the proposed method is a secure steganographic method that provides high hiding capacity and good image quality.     

Color-to-gray conversion using ISOMAP

In this paper we present a new algorithm to transform an RGB color image to a grayscale image. We propose using nonlinear dimension reduction techniques to map higher dimensional color vectors to lower dimensional ones. This approach generalizes the gradient domain manipulation for high dimensional images. Our experiments show that the proposed algorithm generates competitive results and reaches a good compromise between quality and speed.     

一种新的指纹脊线提取方法

本文提出一种新的指纹脊线提取方法。首先利用灰度形态学，结合条件模板进行滤波，然后用Ｏｔｓｕ方法分割得到二值图像，再将原图反相，进行上述同样处理，最后融合两次分割的结果，提取指纹脊线。实验结果证明本法具有抗噪性、旋转不变性。     

模糊相关图割的非监督层次化彩色图像分割

目的 基于阈值的分割方法能根据像素的信息将图像划分为同类的区域,其中常用的最大模糊相关分割方法,因能利用模糊相关度量划分的适当性,得到较好的分割结果,而广受关注。然而该算法存在划分数需预先确定,阈值的分割结果存在孤立噪声,无法对彩色图像实施分割的问题。为此,提出基于模糊相关图割的非监督层次化分割策略来解决该问题。方法 算法首先将图像划分为若干超像素,以提高层次化图像分割的效率;随后将快速模糊相关算法与图割结合,构成模糊相关图割2-划分算子,在确保分割效率的基础上,解决单一阈值分割存在孤立噪声的问题;最后设计了自顶向下层次化分割策略,利用构建的2-划分算子选择合适的区域及通道,迭代地对超像素实施层次化分割,直到算法收敛,划分数自动确定。结果 对Berkeley分割数据库上300幅图像进行了测试,结果表明算法能有效分割彩色图像,分割精度优于Ncut、JSEG方法,运行时间较这两种方法也提高了近20%。结论 本文算法为最大模糊相关算法在非监督彩色图像分割领域的应用提供指导依据,能用于目标检测和识别领域。     

局部自适应的灰度图像彩色化

目的 现有的灰度图像彩色化方法为了保证彩色化结果在颜色空间上的一致性,往往采用全局优化的算法,使得图像边界区域易产生过渡平滑现象。为此提出一种局部自适应的灰度图像彩色化方法,在迁移过程中考虑局部邻域像素信息,同时自动调节邻域像素权重,在颜色正确迁移的同时保证清晰的边界信息。方法 首先结合SVM（support vector machine）和ISLIC（improved simple linear iterative clustering）算法获取彩色图像和灰度图像分类结果图;然后在分类基础上,确定灰度图像高置信度像素点,并根据图像纹理特征,在彩色图像中寻找灰度图像的像素匹配点;最后利用自适应权重均值滤波实现高置信度匹配像素点的颜色迁移,并利用迁移结果对低置信度像素点进行颜色扩散,以完成灰度图像彩色化。结果 实验结果显示,本文方法获得的彩色化迁移结果评分均高于3.5分,特别是局部放大区域评价结果均接近或高于4.0分,高于其他现有彩色化方法评价分数。表明本文方法不仅能够保证颜色迁移的准确性和颜色空间的一致性,同时也能获取颜色区分度高的边界细节信息。与现有的典型灰度图像彩色化方法相比,彩色化结果图在颜色迁移的正确性和抑制边界区域颜色的过渡平滑上都有更优的表现。结论 本文算法为灰度图像彩色化过程中抑制颜色越界问题提供了新的指导方法,能有效地应用于遥感、黑白图像/视频处理、医学图像着色等领域。     

A new approach to morphological color image processing

This paper presents a new approach to the generalization of the concepts of grayscale morphology to color images. A new vector ordering scheme is proposed, infimum and supremum operators are defined, and the fundamental vector morphological operations are extracted. The basic properties of the presented vector morphology are described and its similarities to grayscale morphological operators are pointed out. The main advantages of the proposed methodology are that is vector preserving and provides improved results in many morphological applications. Furthermore, experimental results demonstrate the applicability of the proposed technique in a number of image processing and analysis problems, such as noise removal, edge detection and skeleton extraction.     

Color Sequence Preserving Decolorization

Many visualization techniques use images containing meaningful color sequences. If such images are converted to grayscale, the sequence is often distorted, compromising the information in the image. We preserve the significance of a color sequence during decolorization by mapping the colors from a source image to a grid in the CIELAB color space. We then identify the most significant hues, and thin the corresponding cells of the grid to approximate a curve in the color space, eliminating outliers using a weighted Laplacian eigenmap. This curve is then mapped to a monotonic sequence of gray levels. The saturation values of the resulting image are combined with the original intensity channels to restore details such as text. Our approach can also be used to recolor images containing color sequences, for instance for viewers with color‐deficient vision, or to interpolate between two images that use the same geometry and color sequence to present different data.     

Probabilistic hypergraph based hash codes for social image search

With the rapid development of the Internet, recent years have seen the explosive growth of social media. This brings great challenges in performing efficient and accurate image retrieval on a large scale. Recent work shows that using hashing methods to embed high-dimensional image features and tag information into Hamming space provides a powerful way to index large collections of social images. By learning hash codes through a spectral graph partitioning algorithm, spectral hashing（SH） has shown promising performance among various hashing approaches. However, it is incomplete to model the relations among images only by pairwise simple graphs which ignore the relationship in a higher order. In this paper, we utilize a probabilistic hypergraph model to learn hash codes for social image retrieval. A probabilistic hypergraph model offers a higher order repre-sentation among social images by connecting more than two images in one hyperedge. Unlike a normal hypergraph model, a probabilistic hypergraph model considers not only the grouping information, but also the similarities between vertices in hy-peredges. Experiments on Flickr image datasets verify the performance of our proposed approach.     

Teeth segmentation in digitized dental X-ray films using mathematical morphology

Automating the process of postmortem identification of individuals using dental records is receiving increased attention. Teeth segmentation from dental radiographic films is an essential step for achieving highly automated postmortem identification. In this paper, we offer a mathematical morphology approach to the problem of teeth segmentation. We also propose a grayscale contrast stretching transformation to improve the performance of teeth segmentation. We compare and contrast our approach with other approaches proposed in the literature based on a theoretical and empirical basis. The results show that in addition to its capability of handling bitewing and periapical dental radiographic views, our approach exhibits the lowest failure rate among all approaches studied.     

A comparative study of preprocessing mismatch effects in color image based face recognition

Face color information can play an important role in face recognition (FR) and it can be used to considerably improve FR performance obtained using only grayscale images. The color-based FR methods involve a preprocessing step where a color image is converted into either a monochromatic image or an image having a different color representation. In practical FR systems, the recording or transmission format of the testing images may be arbitrary or inconsistent depending on the application (e.g., face images could consist of grayscale or color pixels either in compressed or uncompressed form). Further, a wide variety of grayscale and color conversions can be used in the preprocessing step. This could lead to a so-called preprocessing mismatch in color-based FR methods: the training and testing face images, generated after preprocessing, do not match in terms of their degree of compression or in terms of their grayscale or color representations. In contrast to grayscale-based FR, a practical color-based FR system has a higher chance of being confronted with a preprocessing mismatch. The aim of this paper is to present a comparative study that addresses the impact of a preprocessing mismatch on color-image based FR methods. We explore three different types of preprocessing mismatches, which practical color-based FR system are highly likely to encounter. In addition, comparative and extensive experiments have been carried out to analyze the effects of the preprocessing mismatches on an FR performance, using Color FRETET, CMU-PIE, AR, and SCface public face databases. The important conclusions drawn from our experiments include: (1) of all color-based FR methods under consideration, color-based FR using feature-level fusion is the most robust approach to preprocessing mismatches; (2) the preprocessing mismatch caused by the use of compressed color images can significantly deteriorate FR performance of color-based FR methods; (3) grayscale testing images can be critical for the feasibility of color-based FR using an input-level fusion; (4) the preprocessing mismatch in terms of grayscale representation has little effect on the FR performances of color-based FR methods.     

基于模糊相似性的彩色形态学图像处理方法

为了将传统灰度图像数学形态学扩展到彩色图像,提出一种结合矢量空间模糊相似性的彩色形态学图像处理方法。首先,在RGB彩色空间中利用彩色矢量间的距离和角度定义模糊相似性测度,以刻画与人类视觉感知相一致的彩色相似程度;以上述相似性测度为准则定义彩色空间中任意一组彩色的上确界和下确界;利用中心像素及其结构单元内像素的上确界和下确界构建彩色形态学的基本操作,包括膨胀、腐蚀、开、闭等操作;进一步将提出的彩色形态学操作应用于高分辨率遥感图像,通过实验对比验证其对地物目标的形变和平滑能力,说明其实用性和有效性。     

彩色图像分形维数的计算方法

分形维数是描述图像复杂性的一种重要测度,广泛应用于图像特征提取及图像分类、分割和检索等方面。多种黑白图像和灰度图像的分形维数计算方法已被提出,但其中很少有适用于彩色图像的分形维数计算方法。把计算灰度图像分形维数的差分盒维法扩展到欧氏五维空间,提出了一种简单且易实现的计算彩色图像分形维数的方法。实验结果表明,提出的方法能够捕捉到彩色图像纹理的复杂性,在识别彩色图像粗糙度变化和计算精度方面优于其它算法。     

New watermarking algorithm utilizing quaternion Fourier transform with advanced scrambling and secure encryption

Digital watermarking technology, as a powerful tool for copyright protection and content authentication of multimedia works, has received increasing attention, and the current image watermarking technology has developed significantly. Generally, embedding a watermark is done in grayscale images, mainly due to the fact that grayscale images are easier to process than color images, and grayscale images only contain brightness information and color-free information, in which an embedded watermark will not produce new color components. In real life, however, color images are more common than grayscale image information. To improve the security of the watermark information and the ability to embed the location and improve the security of the algorithm against a variety of attacks, this paper proposes an algorithm based on quaternion Fourier transform (QFT) with chaotic encryption and Arnold scrambling. Geometric Algebra (GA) can process color images in the form of vectors, and each component of Red,Green and Blue (RGB) should be processed separately. We utilized quaternion (which is a subalgebra of GA) and effectively completed color image processing by utilizing Fourier transform. After utilizing QFT, each component was made more secure by scrambling the pixels of the watermark and performing encryption utilizing chaotic sequencing. Different types of results utilizing Mean Square Error (MSE),Peak Signal to Noise Ratio (PSNR),Structure Similiarity Index Metric (SSIM), etc. were computed to verify the performance of our proposed algorithm and show that the robustness and security are high by utilizing our method.

     

彩色图像统计正交分析方法

彩色图像含有比灰度图像更丰富的信息,因此在图像识别中扮演重要的角色。RGB彩色空间是使用最为广泛的彩色空间。通常R、G、B三分量间存在相关性。彩色图像识别技术的关键是如何有效使用分量间的补信息、消除冗余,并且提取有效的鉴别特征。文中提出了一种新的彩色图像特征提取方法,即彩色图像统计正交分析（CISOA）。该方法按照R、G、B的顺序依次提取三分量的鉴别特征,并保证各分量所提取的特征满足统计正交约束。在彩色人脸和掌纹图像数据库的实验结果表明此方法具有较好的识别效果。     

Virtual double-sided image probing: A unifying framework for non-linear grayscale pattern matching

This paper focuses on non-linear pattern matching transforms based on mathematical morphology for gray level image processing. Our contribution is on two fronts. First, we unify the existing and a priori unconnected approaches to this problem by establishing their theoretical links with topology. Setting them within the same context allows to highlight their differences and similarities, and to derive new variants. Second, we develop the concept of virtual double-sided image probing (VDIP), a broad framework for non-linear pattern matching in grayscale images. VDIP extends our work on the multiple object matching using probing (MOMP) transform we previously defined to locate multiple grayscale patterns simultaneously. We show that available methods as well as the topological approach can be generalized within the VDIP framework. They can be formulated as particular variants of a general transform designed for virtual probing. Furthermore, a morphological metric, called SVDIP (single VDIP), is deduced from the VDIP concept. Some results are presented and compared with those obtained with classical methods.