基于云模型和相容粒的彩色图像检索方法

针对现有相容粒度空间模型中网格点提取只考虑空间位置而忽略图像纹理特征的随机性、模糊性、关联性等不确定性的问题,提出一种基于云模型和相容粒的彩色图像检索方法。首先,在CIELab颜色空间上构建相容粒度空间模型的对象集;其次,用云模型提取每层的网格点,进而构建基于云模型网格点的相容粒度空间模型;然后,提出基于云模型和相容粒的彩色图像检索的相似性度量;最后,用Corel图像库中的图像作为测试图像库进行仿真实验。结果表明,该方法有效地提高了图像的检索效率。     

用全局稳定FCHNN在CIELab色彩空间进行图像分割

在张星明等人所做工作的基础上,进一步从李雅普诺夫稳定性原理出发,改进性地设计了具有全局渐进稳定性和全局指数稳定性的模糊竞争Hopfield神经网络（简称GS-FCHNN）,用GS-FCHNN进行彩色图像分割,从彩色图像在CIELab空间的色彩分布图获得具有明显色差的色彩值,取该值作为模糊核,从而为神经元建立基于最大隶属度原则的状态函数,实现彩色图像的模糊聚类,达到图像目标分割的目的。实验结果表明：较FCHNN算法,运算时间有明显加快,分割效果不受色彩分布的复杂度的影响,对高斯噪声的自适应能力得到进一步加强。     

紫薯酒发酵过程颜色变化规律及颜色特征

研究紫薯酒发酵过程与颜色相关的花色苷含量、褐变指数、聚合色度、总色度及CIELab(Commission Internationale de L'Eclairage制定的L*、a*和b*测量色值的方法)参数变化规律及其相关性,利用CIELab颜色空间比较紫薯酒与蓝莓酒、红白葡萄酒的颜色。结果表明:发酵过程中,褐变指数和聚合色度呈上升趋势,花色苷含量先上升后略下降;总色度与花色苷含量的变化一致且显著正相关性;亮度L*与花色苷含量和色度的变化相反;色度a*和b*分别与褐变指数、聚合色度呈显著负相关性和正相关性。不同种类的酒样,CIELab颜色空间参数不同,表现出不同的颜色特征。     

Colour of hot paprika from the La Vera and Murcia regions packaged in different atmospheres during storage

This study compared the behaviour of hot paprika (Capsicum annuum L.) samples from the district of La Vera and the region of Murcia packaged in five different conditions during storage. The following five different packaging conditions were used in this study: modified atmosphere packaging with three different conditions (100% N₂; 50% N₂ and 50% CO₂; and 100% CO₂), vacuum packaging and traditional packaging (product packaging system without modifying the atmosphere). After the samples were packaged, they were stored for 8 months at room temperature (normal storage conditions). The following parameters were used to indicate the quality of the samples: Aw, ASTA colour, CIE_L*a*b* colour parameters, and the composition of red and yellow compounds. The results indicate that the modified atmosphere packaging and vacuum packaging exerted a protective effect on the paprika quality characteristics regardless of the paprika origin. However, no clear differences were detected between the effect of vacuum packaging and the different modified atmosphere packaging conditions.     

Changes in orange juice color by addition of mandarin juice

The most natural way of improving the color of orange juices is by adding other juices, which provide a more intense coloration. The US legislation allows the addition of up to 10% of mandarin juice to the orange juice to improve its color. The first objective of this study was to compare the color characteristics of juices from 11 mandarin cultivars, currently being grown in Spain. Experimental results proved that only the green-red coordinate, a*, of the orange juices can be improved by adding mandarin juice. The mandarin cultivar that provided a juice with the highest values of a* was Clemenules. Once this selection was made, the effects of adding mandarin juice at different ratios, up to 10%, on the color characteristics of the orange juice were studied. Values of the a* coordinate went from 5.50 for the pure orange juice up to 6.29 for the mixture of 90% orange juice plus 10% of mandarin juice. Finally, hedonic tests proved that regular juice consumers preferred the color of mandarin juice to that of orange juice and that they liked better the color of the juice mixture containing 10% mandarin juice than that containing 3% mandarin juice.     

基于彩色边缘与十字型加权模板的马赛克检测

为了解决高分辨率视频马赛克检测识别率不高的问题,提出了一种基于彩色边缘与十字型加权模板的视频马赛克检测算法.该算法先通过基于CIELab色彩空间的彩色边缘检测检出更多马赛克边缘,再采用十字型加权模板进行模板匹配以识别出马赛克块.采用本文算法以及传统算法对高分辨率视频进行马赛克检测,实验结果表明本文算法对视频中马赛克检测的识别率高达98.2％,相比于传统算法识别率提高了7.1％.     

Mathematical quantification of total carotenoids in Sioma<Superscript>®</Superscript> oil using color coordinates and multiple linear regression during deep-frying simulations

Sioma^® is a variety of red palm oil produced in Ecuador; it is mainly unsaturated, has no flavor, odor, nor cholesterol, and it is GMO-free and free of trans fatty acids. The main objectives of this study were: (a) to study changes in fatty acids, color coordinates, total carotenoids and carotenoid composition during deep-frying simulations; (b) to develop a mathematical model that allows quantification of total carotenoids (antioxidant compounds) using routine color measurements. Two different deep-frying temperatures were assayed 180 and 240 °C. The main fatty acids and carotenoids found in this oil were: (a) oleic, palmitic, and linoleic acids, and (b) α-, β-, and δ-carotenes. During these deep-frying simulations, Sioma^® oil became lighter and more yellowish (L* and b* values increased) and more greenish (a* values decreased); these changes were more evident for higher temperatures. At 180 °C, total carotenoids decreased linearly, from almost 500 mg L^?1, at a rate of 5 mg /kg¹ min^?1; however, at 240 °C the degradation of carotenoids was almost complete after 40 min. Finally, the mathematical models developed using multiple linear regressions allowed an easy and fast quantification of total carotenoids using color measurements.     

基于光场图像序列的自适应权值块匹配深度估计算法

现有的深度估计算法中,针对光场序列图像进行深度估计时,在图像亮度变化较大和弱纹理区域,其匹配效果较差,鲁棒性较低.针对这些问题,本文提出了一种基于CIELab颜色空间的自适应权值块匹配算法.由于彩色图像RGB颜色空间中颜色差异匹配影响因素较多,本算法转换到CIELab空间进行颜色相似性匹配来计算权重值,然后结合梯度和距离计算匹配图像和待匹配图像中匹配块得到综合权重值,最后根据极平面图像（EPI）的线性特性对图像序列中匹配图像和待匹配图像块进行匹配计算,求得深度图.经过仿真验证,本文算法能够较好的估计场景的深度信息,精度上有较大的提升,明显优于以往的深度估计算法,可以广泛使用.     

Evaluation of the storage life of vacuum packaged Australian beef

To establish the shelf-life of vacuum packaged Australian beef, 15 Strip-loins and 15 Cube-rolls for each Processor (A, B, and C) were evaluated at two week intervals (since wk 10 to 20). Steaks on the trays were placed in retail cabinets at 3 °C. Shelf-life evaluation was based on off-odor (only at week 10), microbial analysis, lipid oxidation, and color assessment by trained panelist and Hunter colorimeter. Panelists detected "slightly off-odor" in both primal cuts for Processors B and C (P<0.05). Processor A primal cut steaks displayed better color scores as well as CIE L*, a*, b*, Chroma and Hue values during storage and display period than steaks from the other processors. Also, primal cuts from Processor A showed lower microbial counts and TBARS values with respect to other processors during the trial. Processor A cuts showed improved shelf life attributes initially which helps to explain its slow shelf-life deterioration.