A New Method to Locate the Region of Interest( ROI) of Palmprint

Biometric identification was a kind of identity recognition technology by making use of the human's unique physiological or behavioral characteristics,it provided a high reliability and stability way for the identification. Global threshold binarization palmprint image is used in this paper,and the bio-morphological methods are used to get the sensitive area of palmprint image's positioning point,so as to extract the region of interest. The palmprint collection is realized on the FPGA chip,and this kind of collection method uses the DSP Builder toolbox to realize visual programming in Matlab / Simulink and achieve fast modeling and development. The practice proves that this method is simple,flexible and its equipment is portable and fast.

A New Region-of-interest Coding Method to Control the Relative Quality of Progressive Decoded Images

Based on the ideas of controlling relative quality and rearranging bitplanes, a new ROI coding method for JPEG2000 was proposed, which shifts and rearranges bitplanes in units of bitplane groups. It can code arbitrary shaped ROI without shape coding, and reserve almost arbitrary percent of background information. It also can control the relative quality of progressive decoded images. In addition, it is easy to be implemented and has low computational cost.

Biological Characteristics of Carex brunnescens for Sand Fixation in the Source Region of the Yellow River

Carex brunnescens, a pioneer plant that has an excellent ability to fix sand in the source region of the Yellow River （Maqu）, plays an important role in maintaining the ecosystem stability of alpine grassland in Maqu. In this study, the biological characteristics （phonological characters, the growth process of overground and underground organs, and the morphological characters of underground organs） of C. brunnescens were studied by a field observation experiment. The results showed that C. brunnescens had the characteristics of turning green earlier than other plants, a long growth period, and two flowering and fruiting cycles. The leaf width, length and number of a single plant, and the density, coverage and leaf density of community increased significantly from the leaf extension period to the fruit mature period and then tended to be stable in the withering period, while the plant height and leaf area of a single plant and the leaf area of community rose significantly at first and then decreased. Underground stems （horizontal and vertical stems） and roots of C. brunnescens could survive in sand at a depth of 0-60 cm. The number of middle roots （0.2-0.5 mm in diameter） was the largest in all soil layers （0-20, 20-40 and 40-60 cm）, and the total length of fine roots （〈0.2 mm） were the maximum in the sand at a depth of 20-40 cm, while the total length of middle roots was the maximum in the sand layer at a depth of 0-20 cm. The length, fresh weight and dry weight of the main root, horizontal and vertical stems was the maximum in the sand layer at a depth of 10-30 cm and was the minimum in the sand layer at a depth of 40-50 cm. It is concluded that C. brunnescens can well adapt to the alpine sand habitat of Maqu, can be used as the constructive species for ecological restoration in the alpine desertified grassland of Maqu, and has good popularization and application prospects.

Autonomous Lane Keeping Solution Based on Adaptive Gray Threshold and Region of Interest

Autonomous lane keeping is an important technology in intelligent transportation,which is used to avoid unnecessary traffic accidents caused by lane departure.To adapt different lighting environment,and make up ordinary Hough transform’s shortcomings of tardiness and poor immunity,we propose an improved algorithm by using adaptive gray threshold and setting Region of interest(ROI),to do the quick Hough transform for tracking lane line,implementing autonomous lane keeping. The dynamic adaptive threshold method can be suitable with different lighting conditions and quickly,accurately remove most of the information not relative to lane line.Meanwhile setting ROI can let the program only care about the specific region which can provide useful information and further reduce the processing data.And then on the basic of identification,we put forward some efficient innovation strategy about the control logic of straight state,curve state and the transition state.The experiment proves that this solution greatly raises efficiency.

A mathematical morphological approach for region of interest coding of microscopy image compression

A novel mathematical morphological approach for region of interest(ROI) automatic determination and JPEG2000-based coding of microscopy image compression is presented.The algorithm is very fast and requires lower computing power,which is particularly suitable for some irregular region-based cell microscopy images with poor qualities.Firstly,an active threshold-based method is discussed to create a rough mask of regions of interest(cells).And then some morphological operations are designed and applied to achieve the segmentation of cells.In addition,an extra morphological operation,dilation,is applied to create the final mask with some redundancies to avoid the"edge effect"after removing false cells.Finally,ROI and region of background(ROB) are obtained and encoded individually in different compression ratio flexibly based on the JPEG2000,which can adjust the quality between ROI and ROB without coding for ROI shape.The experimental results certify the effectiveness of the proposed algorithm,and compared with JPEG2000,the proposed algorithm has better performance in both subjective quality and objective quality at the same compression ratios.

图像亮度特征对ROI提取的影响

提出一个基于改进的Itti-Koch模型的感兴趣区域(Region of interest,ROI)提取算法,同时针对图像亮度特征对ROI提取的影响问题,从2个方面进行分析研究:一是根据不同亮度权重下提取的ROI,分析亮度特征对ROI提取的影响程度;二是对眼动数据提取图像的ROI和基于改进的Itti-Koch模型提取的图像ROI进行区域评价,计算两者之间的点对点区域相似度和位置区域相似度。研究结果表明:当亮度特征和颜色特征同时影响图像ROI提取时,亮度特征所占权重不宜超过0.5。

一种新的基于区域增长的ROI分割算法

为克服现有算法带来边缘定位不精确和人工参与太多等缺点,提出了一种新的基于区域增长的适合医学图像中ROI的分割算法。该算法先利用改进的Canny边缘算子进行边缘粗检测,再利用给出的灰度和纹理等信息进行区域增长,最终得到分割图像。为了更好地进行区域增长,新算法通过对ROI中像素的灰度和纹理进行分析,给出结合点向量运算和灰度判断的增长准则。实验结果表明,该方法能对医学图像中复杂区域或畸形区域进行分割,具有很好的鲁棒性与实用性。

一种基于ROI区域生长的医学图像压缩方法

为了克服传统基于ROI的压缩方法提高不了含有狭长的不规则ROI图像的压缩比等缺点,提出一种基于ROI区域生长的医学图像压缩方法。该方法使用区域生长的方法,将医学图像的ROI分割提取后,对ROI和非感兴趣区域(RONI)采用无损和有损相结合的方法,较好地解决了医学图像的高压缩比和高质量的矛盾,缩短了压缩时间。同时该方法还提供了良好的人机交互方式,便于操作,并能够很好地适用于其他场合的压缩。

面向ROI编码的立体图像比特分配策略分析

为了提高基于感兴趣区域（ROI）的立体图像编码的效率，从人眼视觉感知的角度提出了一种探寻合理的立体图像比特分配策略的方法。该方法设计了两个主观实验，其中实验I对各种比特分配策略下的失真立体图像进行视觉质量评价，而实验II在实验I的基础上对所有失真立体图像进行两两对比实验。实验结果表明：合理的比特分配策略对基于ROI的立体图像编码至关重要，且与图像内容无关，但与立体图像质量档次有关；在立体图像ROI采用量化参数（QP）为22、27、32、37的4种不同质量档次编码时，对应的合理分配策略下非ROI与ROI之间QP差异值分别约为9、6、3、3；立体图像ROI与非ROI比特分配策略的确定，能够在保证立体图像整体主观质量不变的同时有效地提高立体图像的编码效率。

ROI的海洋监视卫星遥感图像压缩算法

针对海洋监视卫星遥感图像的特点，提出了一种基于感兴趣区域（ROI）的自适应海洋遥感图像近无损压缩算法。对图像进行了形态Harr小波最大提升后，在一个分辨率低的高频子带中利用阈值和八邻域连通分析方法检测出目标，使用外接矩形与环面的交集来描述ROI，其他分辨率高频子带的ROI通过Mosaic放大得到。高频子带中的ROI采用Rice无损熵编码方法，非ROI进行比特平面编码。低频子带采用DPCM和Rice结合的无损编码方法。实验结果表明，该算法能有效地划分ROI，且没有明显的R01分割痕迹。在中低比特率时，本文算法的峰值信噪比（PSNR）比JPEG2000的高2～5dB，在高比特率时，两者的PSNR均在45dB以上。本文算法计算复杂度低，易于硬件实现，且具有自适应性和数据包独立的优点，适用于海洋监视卫星遥感图像的近无损压缩。

基于ROI提取的多目标图像水平集分割

针对包含多个目标或目标灰度与背景灰度接近的图像分割问题,借鉴人类视觉系统的关注机制和多分辨性,提出一种多尺度框架下基于感兴趣区域提取的图像水平集分割方法。对原图像小波变换的低频分量图应用显著性特征提取出感兴趣区域,将图像域分成多个感兴趣子区域和一个背景子区域,在各目标子区域中,采用C-V模型方法进行曲线演化,并对各子区域分割结果进行合成。仿真结果标明,该算法能有效分割多目标图像。

基于ROI多特征和相关反馈的图像检索算法

本文提出了一种基于感兴趣区域(ROI)综合多特征和相关反馈的图像检索算法。在对图像进行四叉树分解的基础上,由用户选择感兴趣区域,综合颜色、纹理和形状三种底层特征进行多层感兴趣区域检索;由相关反馈技术体现用户感知的主观性,通过调整感兴趣区域、特征间、特征内的权重来提高查准率。给出了改进的CBIR通用模型和特征权重模型。实现了一个图像检索原型系统,将不同实验结果进行了比较和分析,实验结果表明,该文提出的方法具有良好的检索效果。

基于分形与小波的图像ROI自动提取算法

针对分形应用于人造目标作为感兴趣区域的检测中,单一分形特征检测效果不好及计算量大的问题,提出了一种基于分形和小波相结合的图像感兴趣区域提取算法。首先对图像进行小波分解,然后综合利用低频子图像的分形截距特征和拟合误差特征,得到一个新的有效的分形特征参数,从而检测获得低频子图像的感兴趣区域,最后根据原始图像与子图像的坐标对应关系,得到原始图像的感兴趣区域。实验结果表明,该算法能够有效地检测图像感兴趣区域,并且检测速度快。

一种基于上下文的医学图像ROI分类方法

感兴趣区域(ROI)的分类是医学图像的计算机辅助诊断过程的最后一步,传统方法只针对每个ROI区域单独提取特征,再利用统计学习的方法训练分类器进行分类.然而图像中每个区域所包含的视觉特征有限,很难进行准确的分类.文中提出一种基于LDA主题模型的改进模型(LDAC),考虑ROI周围区域,即图像的上下文关系,通过利用LDA对ROI周围区域所包含的上下文信息进行建模,同时结合ROI区域的视觉信息和类别标签,从而辅助ROI区域的分类,以达到提高分类准确率的目的.乳腺图像肿块分类实验表明,文中方法可提高分类的准确性.

基于人眼视觉特性的ROI编码

研究了等级树集分割编码方法(SPIHT)在ROI图像编码中的应用。根据SPIHT编码方法的特性、ROI区域小波系数提升后整幅图像小波系数的特点及人眼视觉特性,提出改进算法。同时提出质量等级因子的概念并给出了其数学表达式。本文提出的改进算法可在保证ROI质量等级的同时提高整幅图像的主观效果。仿真实验证明了改进方法的有效性及质量等级因子的调节作用和其公式的正确性。

基于多级位平面交错的ROI图像编码

在许多的图像应用中 ,基于感兴趣区域 (ROI)图像编码技术占有重要地位。在 ROI图像编码中 ,感兴趣区域采用低压缩比以得到较高的图像质量 ,而背景区域 (ROB)则采用高压缩比以达到相对低一点的图像质量。因此 ,这种技术能很好地解决图像质量和压缩比之间的矛盾。在 JPEG2 0 0 0中已采用了 General Scaling Based Method和Maxshift Method的 ROI编码技术 ,但在一些应用中它们仍不能满足要求。为此提出了一种基于多级位平面交错(MBI)的编码算法。该算法具有多 ROI编码、ROI- ROB重要性编码等特点 。

SAR图像车辆目标ROI的提取技术

SAR图像感兴趣目标区域(Region Of Interest,ROI)的提取是目标识别的基础。该文针对SAR图像中车辆目标ROI提取问题,系统分析了ROI提取过程的关键环节,提出了采用基于有序数据可变索引(Ordered Data Variability Index,ODVI)的自适应CFAR方法实现目标的恒虚警检测,同时对ROI切片计算鉴别特征,并实现序贯鉴别。最后利用X波段SAR图像数据验证了该文的ROI提取技术,给出了鉴别输出的ROI,处理结果显示该文算法能准确提取车辆目标ROI,有效消除虚警。

一种新的掌纹ROI图像定位方法

在分析传统Harris算法缺陷的基础上,提出一种基于角点检测的快速掌纹图像预处理方法。该方法利用一种改进的自适应Harris算法提取出手掌边缘和手指凹凸处的轮廓特征点,采用属于同一特征组的特征点均值作为候选角点,剔除了邻近角点,并根据候选角点在轮廓线上角度变化的大小定位手指根部的三个关键角点,从而有效提取出掌纹图像的感兴趣区域(ROI)。实验测试图像采用CASIA数据库,实验结果表明,该方法能快速有效地定位出掌纹的ROI区域,且能有效增强掌纹图像的边缘与细节,有利于提高掌纹识别的识别率。

基于SURF的月球影像ROI检测

根据月球影像的光照特点,分析了月球影像的感兴趣区域(ROI)特点与局部视觉特征的关系,构建了基于快速鲁棒性特征(SURF)的月球影像撞击坑模型.在此基础上提出了月球影像ROI检测算法:提取月球影像中撞击坑明亮面与阴影面的SURF点,合并相互交叠的同质区域,依据月球影像撞击坑模型的构建约束进行明暗特征对组合,形成ROI.针对嫦娥一号及嫦娥二号月球影像数据进行ROI检测,实验结果表明基于SURF的月球影像ROI检测方法能准确地提取影像中显著的撞击坑区域,检测效果明显好于经典的Itti检测方法.

SAR图像的ROI特征配准方法

SAR图像配准是SAR图像处理的关键技术,对SAR图像的融合、拼接等有着深刻影响。SAR图像的配准中基于区域的配准方法往往存在区域提取困难,受相干斑影响较大等缺陷。本文提出了一种基于ROI特征的SAR图像自动配准方法。该方法提取SAR图像中的ROI特征作为配准基元,将行、列匹配概率系数与不变矩最小距离测度相结合进行特征匹配,利用所有正确匹配的ROI特征对的质心坐标和最小二乘算法估计仿射变换模型参数。用实际SAR图像测试该方法,并与多种已有的方法进行比较,实验结果表明:该方法具有很好的适应性和配准精度。