Human iris feature extraction under pupil size variation using local texture descriptors

Multimedia Tools and Applications - The human iris texture is one of the most reliable biometric traits because it is unique, and the iris pattern remains stable for years. However, iris images...     

基于视频动态纹理的火灾检测

长期以来,森林火灾检测一直都是世界范围内的一个重要研究课题,对于保护地球环境及人类安全都有重要意义.基于视频监控的火灾检测对于实时性和正确性要求很高,而传感式探测器和传统图像型探测器不能满足要求.提出了一种基于动态纹理特征分析的新型图像型火灾检测算法,对于森林这样的复杂大空间场景尤为适用.通过对CCD摄像机拍摄的视频图像,建立线性动力系统(LDS)模型,分析其动态纹理特征,最后利用Adaboost分类器判断火灾是否存在.实验结果表明,此算法能够达到95％的检测准确率,且具有较好的应用前景.     

利用模糊认知度从图像纹理中提取情感语义

图像的低层视觉特征（颜色、纹理和形状等）中包含着大量人类可感知的情感语义信息。利用纹理特征,提出一种新的索引方法-FRD（Fuzzy Recognize Degree,模糊认识度）聚类法,用来描述与情感相关联的语义图像。FRD聚类法使用三个感性的纹理特征：方向性、对比度和粗糙度,生成FRD值。从高层的情感概念进行图像检索。实验图像采用自然景观图片,验证了新方法的良好性能。     

An efficient color and texture based iris image retrieval technique

This paper proposes a hierarchical approach to retrieve an iris image efficiently from for a large iris database. This approach is a combination of both iris color and texture. Iris color is used for indexing and texture is used for retrieval of iris images from the indexed iris database. An index which is determined from the iris color is used to filter out the images that are not similar to the query image in color. Further, iris texture features of those filtered images, are used to determine the images which are similar to the query image. The iris color information helps to design an efficient indexing scheme based on color indices. The color indices are computed by averaging the intensity values of all red and blue color pixels. Kd-tree is used for real-time indexing based on color indices. The iris texture features are obtained through Speeded Up Robust Features (SURF) algorithm. These features are used to get the query’s corresponding image at the top best match. The performance of the proposed indexing scheme is compared with two well known iris indexing schemes ( [Mehrotra et al., 2010] and [Puhan and Sudha, 2008]) on UPOL (Dobeš, Machala, Tichavský, & Posp?´šil, 2004) and UBIRIS (Proencca & Alexandre, 2005) iris databases. It is observed that combination of iris color and texture improves the performance of iris recognition system.     

动态视频序列下的坦克车体姿态识别

敌方坦克的姿态信息是装甲分队武器目标分配的重要依据,但目前坦克火控系统中并没有姿态识别的模块,为此提出一种基于压缩跟踪和级联分类器的动态视频序列下坦克车体姿态识别方法。将压缩跟踪算法的输出作为级联分类器的输入,缩小姿态识别的范围并减小分类器对不同环境中负样本的依赖;将坦克车体姿态分为12组,训练了12个分类器,在训练中引入了车体的轮廓信息;将多个级联分类器串联工作,识别坦克车体的多个姿态。对比了检测不同姿态的分类器的识别效果,结果表明级联分类器能以一定的精度对在真实环境中的坦克姿态进行识别。     

Fuzzy triangulation signature for detection of change in human emotion from face video image sequence

The present article proposes a geometry-based fuzzy relational technique for capturing gradual change in human emotion over time available from relevant face image sequences. As associated features, we make use of fuzzy membership arising out of five triangle signatures such as - (i) Fuzzy Isosceles Triangle Signature (FIS), (ii) Fuzzy Right Triangle Signature (FRS), (iii) Fuzzy Right Isosceles Triangle Signature (FIRS), (iv) Fuzzy Equilateral Triangle Signature (FES), and (v) Other Fuzzy Triangles Signature (OFS) to achieve the task of appropriate classification of facial transition from neutrality to one among the six expressions viz. anger (AN), disgust (DI), fear (FE), happiness (HA), sadness (SA) and surprise (SU). The effectiveness of the Multilayer Perceptron (MLP) classifier is tested and validated through 10 fold cross-validation method on three benchmark image sequence datasets namely Extended Cohn-Kanade (CK+), M&M Initiative (MMI), and Multimedia Understanding Group (MUG). Experimental outcomes are found to have achieved accuracy to the tune of 98.47%, 93.56%, and 99.25% on CK+, MMI, and MUG respectively vindicating the effectiveness by exhibiting the superiority of our proposed technique in comparison to other state-of-the-art methods in this regard.

     

Real-time emotion retrieval scheme in video with image sequence features

In the current Internet environment, a lot of multimedia information is navigated on the on-line computer systems. Among the multimedia information, video sequence has the most valuable and meaningful influence on human emotions. Therefore, one human’s emotions to see and feel the same video can be different from that of others depending on the person’s mental state. In this research, we propose a new real-time emotion retrieval scheme in video with image sequence features. The features of image sequence consist of color information, key frame extraction, video sound, and optical flow. Each video feature is combined with the weight for the emotion retrieval. The experimental results show the new approach of real-time emotion retrieval in video with the better results compared to the previous studies. The proposed scheme will be applied to the many multimedia fields: movie, computer game, video conference, and so on.     

视频图像变化信息的动态检测算法与实现

研究了一种视频图像变化信息动态检测的方法。该方法采用数字图像处理技术，将中值滤波和自适应阈值分割应用到了检测当中。同时提出了分区域帧间比较的思想，以计算机为工作平台进行移动侦测，较好的解决虚警和漏警问题，有较高的准确性和可靠性。     

视频图像变化信息的动态检测算法与实现

研究了一种视频图像变化信息动态检测的方法。该方法采用数字图像处理技术,将中值滤波和自适应阈值分割应用到了检测当中。同时提出了分区域帧间比较的思想,以计算机为工作平台进行移动侦测,较好的解决虚警和漏警问题,有较高的准确性和可靠性。     

Detecting salient objects in non-stationary video image sequence for analyzing user perceptions of digital video contents

Multimedia Tools and Applications - The ubiquitous utilization of video applications in recent years has made research on video quality of experience paramount. Lack of sufficient bandwidth deters...     

基于动态范围扩展的海底视频图像增强算法

水下视频成像是海洋探测的关键技术,但是海底的特殊环境造成海底图像存在细节模糊、光照不均等问题。为此提出一种基于动态范围扩展的海底视频图像增强算法,该算法可以同时处理因光照不均而引起的图像曝光过度和曝光不足现象。首先,构造映射函数判断图像曝光过度和曝光不足的区域;然后,计算图像的动态范围,利用图像的“闲置空间”对图像曝光过度和曝光不足区域同时进行动态扩展;最后将图像转换到YCbCr空间对扩展后的图像进行亮度通道的直方图均衡化。实验结果表明,和已有算法比较,新算法既可以避免传统的直方图均衡化产生的图像过增强,提高了图像的清晰度,又可以修复图像因光照不均丢失的像素信息,显著改善图像细节。     

A universal texture segmentation and representation scheme based on ant colony optimization for iris image processing

This paper proposes a novel scheme for texture segmentation and representation based on Ant Colony Optimization (ACO). Texture segmentation and texture characteristic expression are two important areas in image pattern recognition. Nevertheless, until now, how to find an effective way for accomplishing these tasks is still a major challenge in practical applications such as iris image processing. We propose a framework for ACO based image processing methods. Considering the specific characteristics of various tasks, such a framework possesses the flexibility of only defining different criteria for ant behavior correspondingly. By defining different kinds of direction probability and movement difficulty for artificial ants, an ACO based image segmentation algorithm and a texture representation method are then presented for automatic iris image processing. Experimental results demonstrated that the ACO based image processing methods are competitive and quite promising, with excellent effectiveness and practicability especially for images with complex local texture situations.     

Video collage: presenting a video sequence using a single image

The explosive growth of video data demands the video presentation technique which supports fast browsing of video content. In this paper, we present an automatic procedure for constructing a compact synthesized collage from a video sequence. The synthesized image, called “Video Collage”, is a kind of static video summary—to select the most representative images from video, to extract salient regions of interest (ROIs) from these images, and to seamlessly arrange ROIs on a given canvas with the temporal structure of video content preserved. We formulate the generation of Video Collage as a unified energy minimization problem in which each of above desirability is represented by an energy term. We start from the basic setting of Video Collage in which both the shape of ROIs and collage are fixed as rectangular, and then show how it can support arbitrary shapes of ROIs, as well as a variety of collage templates and region of interest (ROI) arrangement layouts (i.e., book, diagonal, and spiral). The experiments show its effectiveness to present a video in a very compact and visually appealing form while preserving the necessary information to understand the video.

Using texture to complement color in image matting

Current image matting methods based on color sampling use color to distinguish between foreground and background pixels. However, they fail when the corresponding color distributions overlap. Other methods that define correlation between neighboring pixels based on color aim to propagate the opacity parameter α from known pixels to unknown pixels. However, strong edges of textured regions may block the propagation of α. In this paper, a new matting strategy is proposed that delivers an accurate matte by considering texture as a feature that can complement color even if the foreground and background color distributions overlap and the image is a complex one with highly textured regions. The texture feature is extracted in such a way as to increase distinction between foreground and background regions. An objective function containing color and texture components is optimized to find the best foreground and background pair among a set of candidate pairs. The effectiveness of proposed method is compared quantitatively as well as qualitatively with other matting methods by evaluating their results on a benchmark dataset and a set of complex images. The evaluations show that the proposed method presented the best among state of the art matting methods.     

数字图像合成器欺骗式干扰的识别方法

分析了数字图像合成器（DIS）生成的目标图像与真实目标图像之间的异同点,经过推导,得出识别数字图像合成器欺骗式干扰的方法：由于相位增量量化导致欺骗式假目标在横向多普勒方向上图像不连续;脉冲重复频率不匹配时,由DIS生成的欺骗式假目标经ISAR处理后在成像视窗内目标数量会发生变化。从而发现了数字图像合成器欺骗式干扰的缺陷,对识别这种干扰的假目标具有决定意义。