Automatic Detection of Lung Infection Basha, CMAK Zeelan; Krishna, Azmira; Savarapu, Pradeep Raj
International journal of recent technology and engineering,
09/2019, Letnik:
8, Številka:
3
Journal Article
Odprti dostop
Analysis Of Lung Infected Images By Clustering Basic Algorithms Together For Detecting The Lung Infected Area. We Used K-Means Algorithm In An Image To Detect The Infected Area. This Algorithm ...Separates All The Different Complexions Of Color In The Given Lung Image. By This The Infected Region Of The Lung Can Be Obtained After A Series Of Image Clusters.
Sorghum seeds can discolor during storage. Treatment of seeds with citric acid improves sensory quality and antioxidant activity. This study compared the differences in phenotypic and antioxidant ...activity between citric acid-treated and water-treated sorghum seeds. The study used transcriptomics and metabolomics approaches to investigate the regulatory mechanisms. The ∆a, ∆b and ∆l values of citric acid-treated sorghum seeds significantly increased after 6 months of storage. The SOD, POD and CAT enzyme activities of the citric acid-treated group were 1.94, 1.91 and 2.45 times higher than those of the control, respectively. The joint transcriptome and metabolome analysis showed that the citric acid-induced changes were mainly focused on the flavonoid biosynthetic pathway. Citric acid treatment up-regulated CHS, ANR, MYB and bHLH genes and promoted flavonoid accumulation. In conclusion, citric acid treatment promotes flavonoid accumulation, delays sorghum seed discoloration, and enhances antioxidant activity and storage life.
CIELAB color paths during meat shelf life Hernández Salueña, Begoña; Sáenz Gamasa, Carlos; Diñeiro Rubial, José Manuel ...
Meat science,
November 2019, 2019-Nov, 2019-11-00, 20191101, Letnik:
157
Journal Article
Recenzirano
Meat color evolution from freshly cut to beyond shelf life, up to 40% of metmyoglobin, has been theoretically modeled using the Kubelka-Munk theory and a set of measured reference reflectance spectra ...of deoxymyoglobin, oxymyoglobin and metmyoglobin. Color evolution depicts characteristic color paths in CIELAB color space. During oxidation the model explains the approximately constancy of L*, b* and hab, with variations typically hidden by sample dispersion, and the special significance of a* and C* in relation with metmyoglobin formation. CIELAB ΔE* color difference and the reflectance ratio R630/R580 are even better indicators of metmyoglobin changes during oxidation. The role of a*, C*, ΔE* and R630/R580 and their relationship during oxidation is a normal feature in the model with quantitative predictions in general agreement with literature. Results further emphasize the dangers of reporting color coordinates in different illuminants.
•Meat color is well explained by DMb + OMb (oxygenation) and OMb + MMb (oxidation).•Meat oxygenation and oxidation determine characteristic paths in CIELAB color space.•Sample variance typically hinders changes in L*, b* and hab caused by MMb increase.•ΔE* and R630/R580 are better tracers of MMb increase than a* and C*.•Different illuminants give different color values but similar color evolution.
The International Commission on Illumination (CIE) designed its color space to be perceptually uniform so that a given numerical change in the color code corresponds to perceived change in color. ...This color encoding is demonstrated to be advantageous in scientific visualization and analysis of vector fields. The specific application is analysis of ice motion in the Arctic where patterns in smooth monthly-averaged ice motion are seen. Furthermore, fractures occurring in the ice cover result in discontinuities in the ice motion. This vector jump in displacement can also be visualized. We then analyze modeled and observed fractures through the use of a metric on the color space, and image amplitude and phase metrics. Amplitude and phase metrics arise from image registration that is accomplished by sampling images using space filling curves, thus reducing the image registration problem to the more reliable functional alignment problem. We demonstrate this through an exploration of the metrics to compare model runs to an observed ice crack.
•A novel use of color is presented for scientific analysis and visualization.•Applications to color encoding of vector fields show utility of the color map.•Image registration is used to analyze localized sea ice fractures (leads).•An image registration technique using space filling curves reliably aligns images.•A new image amplitude metric and image phase measure can be used in parameter calibration.
Quality evaluation of underwater images is a key goal of underwater video image retrieval and intelligent processing. To date, no metric has been proposed for underwater color image quality ...evaluation (UCIQE). The special absorption and scattering characteristics of the water medium do not allow direct application of natural color image quality metrics especially to different underwater environments. In this paper, subjective testing for underwater image quality has been organized. The statistical distribution of the underwater image pixels in the CIELab color space related to subjective evaluation indicates the sharpness and colorful factors correlate well with subjective image quality perception. Based on these, a new UCIQE metric, which is a linear combination of chroma, saturation, and contrast, is proposed to quantify the non-uniform color cast, blurring, and low-contrast that characterize underwater engineering and monitoring images. Experiments are conducted to illustrate the performance of the proposed UCIQE metric and its capability to measure the underwater image enhancement results. They show that the proposed metric has comparable performance to the leading natural color image quality metrics and the underwater grayscale image quality metrics available in the literature, and can predict with higher accuracy the relative amount of degradation with similar image content in underwater environments. Importantly, UCIQE is a simple and fast solution for real-time underwater video processing. The effectiveness of the presented measure is also demonstrated by subjective evaluation. The results show better correlation between the UCIQE and the subjective mean opinion score.
Abstract Leaf Area Index (LAI) is the ratio of ground surface area covered by leaves. LAI plays a significant role in the structural characteristics of forest ecosystems. Therefore, an accurate ...estimation process is needed. One method for estimating LAI is using Digital Cover Photography. However, most applications for processing LAI using digital photos do not consider the brown color of plant parts. Previous research, which includes brown color as part of the calculation, potentially produced biased results by the increased pixel count from the original photo. This study aims to enhance the accuracy of LAI estimation. The proposed methods consider the brown color while minimizing errors. Image processing is carried out in two stages to separate leaves and non-leaf pixels by using the RGB color model for the first stage and applying the CIELAB color model in the second stage. Proposed methods and existing applications are evaluated against the actual LAI value obtained using Terrestrial Laser Scanning (TLS) as the ground truth. The results demonstrate that the proposed methods effectively identify non-leaf parts and exhibit the lowest error rates compared to other methods. In conclusion, this study provides alternative techniques to enhance the accuracy of LAI estimation in forest ecosystems.
Resumo O Índice de Área Foliar (IAF) é a razão da área da superfície do solo coberta por folhas. O IAF desempenha um papel significativo nas características estruturais dos ecossistemas florestais. Portanto, é necessário um processo de estimativa preciso. Um método para estimar o IAF é o uso da Fotografia de Cobertura Digital. No entanto, a maioria das aplicações para processamento do IAF usando fotos digitais não considera a cor marrom das partes das plantas. Pesquisas anteriores, que incluem a cor marrom no cálculo, potencialmente produziram resultados enviesados devido ao aumento na contagem de pixels da foto original. Este estudo tem como objetivo aprimorar a precisão da estimativa do IAF. Os métodos propostos consideram a cor marrom enquanto minimizam erros. O processamento de imagem é realizado em duas etapas para separar os pixels de folhas e não folhas, usando o modelo de cor RGB na primeira etapa e aplicando o modelo de cor CIELAB na segunda etapa. Os métodos propostos e as aplicações existentes são avaliados em relação ao valor real do IAF obtido por meio da Varredura a Laser Terrestre (TLS) como referência. Os resultados demonstram que os métodos propostos identificam efetivamente as partes não foliares e apresentam as menores taxas de erro em comparação com outros métodos. Concluindo, este estudo oferece técnicas alternativas para aprimorar a precisão da estimativa do IAF em ecossistemas florestais .
In the present study, the colour and C:N ratio of quinoa flours pigmented with M. purpureus supplemented with monosodium glutamate and sodium chloride were evaluated during 14 days of fermentation. ...The best values of L*, a* and b* corresponded to the eighth day. This research showed that the pigmented flour produced by solid state fermentation of quinoa by M. purpureus showing variations in the colour red along with the C:N ratio during the fermentation time, resulting in a product with good visual sensory attributes that can be used to develop new naturally pigmented products with potential functional characteristics.
The majority of rosé wines are bottled in clear bottles as color is an important factor in consumer preference. Post-bottling wine can be exposed to UV-visible light and temperature fluctuations ...resulting in quality degradation. This study investigated the impact of bottle color (flint and antique green), light exposure (darkness, LED and fluorescent bulb), and temperature (12 °C and 22 °C) on rosé wine quality using a full factorial design with three different wines (Grenache, Pinot noir and Zinfandel). The impact on chemical composition, color, phenolics and aromatics was determined. Projective mapping was carried out for sensorial analysis. Changes in the aromatics, color and phenolic composition were detectable after three months and more noticeable after six months of storage. Overall, all variables studied impacted rosé wine characteristics significantly. However, higher temperature in combination with clear glass bottles under fluorescent light were the most detrimental conditions.
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