基于双目视觉的机器人目标定位与机械臂控制

为了更好地与复杂多变的非结构化环境进行交互,完成对目标物体的识别和抓取,提出了一种应用于服务机器人平台的基于双目视觉的仿人机械臂控制方法.文中首先用D-H方法对机械臂进行建模,并对这个模型做了改进,给出了一种更加简便的3+1自由度仿人机械臂的逆解算法,采用基于双目视觉与颜色分割的目标识别方法;然后根据识别出的目标三维坐标信息控制机械臂完成抓取任务;最后,本方法在家庭服务机器人上得到了验证,机器人能够完成对目标物体的识别和抓取动作.     

基于HSV 色彩空间与数学形态学的车牌定位研究

车牌识别系统在高速路收费口与住宅小区车库管理中得到越来越多的应 用,车牌定位是整个识别系统实现的前提。基于灰度图像的定位方法和基于彩色车牌图像的 定位方法,实现效果均不大理想。在充分利用车牌先验信息的基础上,提出基于HSV 色彩 空间与数学形态学的车牌定位方法。先利用色彩信息对可能包含车牌目标的区域进行过滤, 再利用数学形态学技术生成连通区域,判断并生成正确的车牌区域,最后,使用radon 变换进 行倾斜校正。     

基于颜色空间转换的运动目标检测与阴影去除

针对室内视频监控中运动目标检测常出现的阴影误检,提出了一种基于颜色空间转换的自适应背景建模和阴影消除算法.在RGB空间采用自适应背景差对视频图像进行前景背景分离,并将检测出的前景目标锁定在活动轮廓矩形框内进行目标跟踪,对于误检的虚假目标(即阴影),利用其亮度等信息,在HSV空间去除.经实验验证,该算法对阴影的去除有良好的效果,能准确检测出真实目标.     

基于引导滤波的Retinex快速夜间彩色图像增强技术

针对目前基于Retinex原理的图像增强技术在对夜间彩色图像处理中存在颜色失真、在高对比度边缘区域存在“光晕伪影”等问题, 提出了一种基于引导滤波的Retinex快速夜间彩色图像增强的算法.该算法首先构造优化的颜色恢复函数, 然后对夜间彩色图像在色调、饱和度、亮度(hue, saturation, value, HSV)颜色空间下的亮度图像采用具有边缘保持功能的引导滤波进行平滑处理, 估计场景的光照分量, 进而获得仅包含物体本身特性的反射分量图像, 经过Gamma校正与颜色恢复后最终实现夜间彩色图像增强.实验结果表明, 本文提出的算法增强效果显著、效率较高, 同时具有颜色保真、抑制过增强和能较好保留边缘细节信息等特性.     

Cytoprotective effects of geraniin against peroxynitrite- and peroxyl radical-induced cell death via free radical scavenging activity

The role of natural antioxidants in combating the deleterious effects of free radicals has received much attention. In the present study, the cytoprotective effects and the free radical scavenging activity of geraniin, a hydrolysable ellagitannin from Nephelium lappaceum rind, were evaluated by using various approaches. Addition of geraniin to the culture media resulted in a profound cytoprotective effect against damages induced by the peroxynitrite generator 3-morpholinosydnonimine (SIN-1), and the peroxyl radical generator 2,2′-azobis(2-amidinopropane) dihydrochloride (AAPH). Geraniin exhibits more potent cytoprotective activity than that of 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox). Geraniin exhibited potent antioxidant activity against reactive species, such as nitric oxide, superoxide anion, and chemically synthesized peroxynitrite. Kinetic analysis of reactivity against peroxyl radicals generated by AAPH revealed that geraniin possesses potent reactivity against peroxyl radicals with higher stoichiometric number than Trolox. The cytoprotective effect of geraniin was only observed when geraniin and these toxic compounds were co-existing, suggesting that geraninn exhibits cytoprotective effects via free radical scavenging activity in the extracellular fluid.     

基于彩色分量垂直边缘检测的车牌定位新方法

考虑车牌本身特征,选择HSV和RGB颜色模型,并对每个分量的贡献值进行分析研究;选取一种有利于车牌提取的颜色空间及一组空间分量的权重值,利用设计的垂直方向算子得到车牌边缘信息,设计了一种阈值选取方法进行二值化处理,最后使用投影积分方法进行车牌细定位。通过各种情况下在卡口获取的200幅车辆实测图像进行测试,车牌定位的准确性和鲁棒性都较好。     

基于HSV色彩空间的图像分割

为了辨识和分析目标,需要将这些有关区域分离出来,在此基础上才有可能对目标进一步处理。本文提出了一种利用HSV色彩空间的图像分割方法,根据HSV色彩空间的颜色和亮度无关,将彩色图像从RGB空间变换到HSV空间,然后经过H分割对绿地植被信息进行提取得到分割结果。实验表明该方法具有很强的鲁棒性。     

基于HSV分块颜色直方图的图像检索算法

针对基于颜色的图像检索问题,提出了一种新的基于HSV非均匀量化分块颜色直方图的图像检索方法。分块直方图算法把图像固定分成若干子块,分别计算子块的颜色特征。将含有重要空间信息的分块设置权值,并将不注重空间信息的分块权值设为零：此算法充分利用了HSV非均匀量化和图像分块的优点,改善了颜色特征缺乏空间信息的缺点。研究结果表明,基于HSV非均匀量化分块颜色直方图的算法相对于全局颜色直方图有较好的检索精度。     

马尔科夫随机场模型下的Retinex夜间彩色图像增强

由于Retinex算法在处理夜间彩色图像时容易出现光晕、颜色失真、细节丢失与噪声干扰等问题,本文基于马尔科夫随机场（MRF）提出了一种针对单幅图像的Retinex图像增强算法。该算法在HSV颜色空间下采用线性引导滤波估计图像照度分量;在MRF模型下求解仅包含物体本身特性的反射分量,并通过颜色恢复函数与增益补偿方法进行颜色恢复与校正,最终实现了夜间彩色图像的增强。实验结果表明,利用本文算法处理后图像的均值（整体亮度）可以提高2倍以上,标准差、熵、峰值信噪比（PSNR）等参数均有5%以上的提升。与其它基于Retinex原理的算法相比,本文提出的算法增强效果显著,具有消除“光晕伪影”现象、抑制噪声、颜色保真和有效地凸显边缘细节信息等能力。     

Plasmodium species aware based quantification of malaria parasitemia in light microscopy thin blood smear

Malaria is a serious worldwide disease, caused by a bite of a female Anopheles mosquito. The parasite transferred into complex life round in which it is grown and reproduces into the human body. The detection and recognition of Plasmodium species are possible and efficient through a process called staining (Giemsa). The staining process slightly colorizes the red blood cells (RBCs) but highlights Plasmodium parasites, white blood cells and artifacts. Giemsa stains nuclei, chromatin in blue tone and RBCs in pink color. It has been reported in numerous studies that manual microscopy is not a trustworthy screening technique when performed by nonexperts. Malaria parasites host in RBCs when it enters the bloodstream. This paper presents segmentation of Plasmodium parasite from the thin blood smear points on region growing and dynamic convolution based filtering algorithm. After segmentation, malaria parasite classified into four Plasmodium species: Plasmodium falciparum, Plasmodium ovale, Plasmodium vivax, and Plasmodium malaria. The random forest and K‐nearest neighbor are used for classification base on local binary pattern and hue saturation value features. The sensitivity for malaria parasitemia (MP) is 96.75% on training and testing of the proposed approach while specificity is 94.59%. Beside these, the comparisons of the two features are added to the proposed work for classification having sensitivity is 83.60% while having specificity is 94.90% through random forest classifier based on local binary pattern feature.