874 resultados para Color extraction


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Polyester fibers are the most used fibers in the world and disperse dyes are used for dyeing these fibers. After dyeing, the colorful dyebath is discharged into effluent streams, which needs a special treatment for color removal. Surfactants interaction with dyes has been evaluated in several studies, including the textile area, specifically in the separation of dyes from textile wastewater. In this work a cationic surfactant was used in a microemulsion system for the extraction of anionic dyes (disperses dyes) from textile wastewater. These microemulsion system was composed by dodecylamonium chloride (surfactant), kerosene oil (organic phase), isoamyl alcohol (cosurfactant) and the wastewater (aqueous phase). The wastewater that results after the dyeing process is acid (pH 5). It was observed that changing the pH value to above 12.8 the extraction could be made, resulting in an aqueous phase with low color level. The Scheffé net experimental design was used for the extraction process optimization, and the obtained results were evaluated using the program "Statistica 7.0". The optimal microemulsion system was composed by 59.8wt.% of wastewater, 30.1wt.% of kerosene, 3.37wt.% of surfactant and 6.73wt.% of cosurfactant, providing extraction upper than 96%. A mix of reactive dyebath (50%) and disperse dyebath (50%) was used as aqueous phase and it presented extraction upper than 98%. The water phase after extraction process can be reused in a new dyeing, being obtained satisfactory results, according to the limits established by textile industry for a good dyeing. Tests were accomplished seeking to study the influence of salt addition and temperature. An experimental design was used for this purpose, which showed that the extraction doesn't depend on those factors. In this way, the removal of color from textile wastewater by microemulsion is a viable technique (that does not depend of external factors such as salinity and temperature), being obtained good extraction results even with in wastewater mixtures

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Efficient optic disc segmentation is an important task in automated retinal screening. For the same reason optic disc detection is fundamental for medical references and is important for the retinal image analysis application. The most difficult problem of optic disc extraction is to locate the region of interest. Moreover it is a time consuming task. This paper tries to overcome this barrier by presenting an automated method for optic disc boundary extraction using Fuzzy C Means combined with thresholding. The discs determined by the new method agree relatively well with those determined by the experts. The present method has been validated on a data set of 110 colour fundus images from DRION database, and has obtained promising results. The performance of the system is evaluated using the difference in horizontal and vertical diameters of the obtained disc boundary and that of the ground truth obtained from two expert ophthalmologists. For the 25 test images selected from the 110 colour fundus images, the Pearson correlation of the ground truth diameters with the detected diameters by the new method are 0.946 and 0.958 and, 0.94 and 0.974 respectively. From the scatter plot, it is shown that the ground truth and detected diameters have a high positive correlation. This computerized analysis of optic disc is very useful for the diagnosis of retinal diseases

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A process has been elaborated for one-step low lignin content sugarcane bagasse hemicellulose extraction using alkaline solution of hydrogen peroxide. To maximize the hemicellulose yields several extraction conditions were examined applying the 2(4) factorial design: H(2)O(2) concentration from 2 to 6% (w/v), reaction time from 4 to 16 h, temperature from 20 to 60 degrees C, and magnesium sulfate absence or presence (0.5%, w/v). This approach allowed selection of conditions for the extraction of low and high lignin content hemicellulose. At midpoint the yield of hemicellulose was 94.5% with more than 88% of lignin removed. Lignin removal is suppressed at low extraction temperatures and in the absence of magnesium sulfate. Hemicellulose in 86% yield with low lignin content (5.9%) was obtained with 6% H(2)O(2) treatment for 4 h and 20 degrees C. This hemicellulose is much lighter in color than samples obtained at the midpoint condition and was found suitable for subsequent enzymatic hydrolysis. (C) 2009 Elsevier B.V. All rights reserved.

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With the increase of use of digital media the need for the methods of multimedia protection becomes extremely important. The number of the solutions to the problem from encryption to watermarking is large and is growing every year. In this work digital image watermarking is considered, specifically a novel method of digital watermarking of color and spectral images. An overview of existing methods watermarking of color and grayscale images is given in the paper. Methods using independent component analysis (ICA) for detection and the ones using discrete wavelet transform (DWT) and discrete cosine transform (DCT) are considered in more detail. A novel method of watermarking proposed in this paper allows embedding of a color or spectral watermark image into color or spectral image consequently and successful extraction of the watermark out of the resultant watermarked image. A number of experiments have been performed on the quality of extraction depending on the parameters of the embedding procedure. Another set of experiments included the test of the robustness of the algorithm proposed. Three techniques have been chosen for that purpose: median filter, low-pass filter (LPF) and discrete cosine transform (DCT), which are a part of a widely known StirMark - Image Watermarking Robustness Test. The study shows that the proposed watermarking technique is fragile, i.e. watermark is altered by simple image processing operations. Moreover, we have found that the contents of the image to be watermarked do not affect the quality of the extraction. Mixing coefficients, that determine the amount of the key and watermark image in the result, should not exceed 1% of the original. The algorithm proposed has proven to be successful in the task of watermark embedding and extraction.

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β-glucan is currently one of the most important bioactive substances. Hence, there is a growing interest in the production of various foods containing β-glucan. The study examines the influence of the degree of wheat flour extraction in the quality of breads with high β-glucan content. Rheological tests were conducted on dough. Volume, mass, color and texture of bread were measured after baking. We observed that increasing the degree of extraction caused an increase in the storage and loss modulus. All of the bread made from the different flours were smaller in volume after the addition of β-glucan, although the yield increased. The crumb color of β-glucan-added breads was darker than the control samples. Control samples were higher in textural parameters (firmness, gumminess and chewiness). β-glucan-added samples had decreased porosity. The results revealed that using very strong flour with a high protein content results in a high quality β-glucan bread with a higher nutritional value due to the high total dietary fiber and β-glucan content.

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AbstractPurple sweet potato (PSP) can provide products with attractive color besides nutritious benefits in food processing. So, the compositions and color stability of an aqueous anthocyanin-based PSP extract were investigated in order to promote its wide use in food industry. PSP anthocyanins were extracted with water, and nine individual anthocyanins (48.72 ug mL–1 in total, 24.36 mg/100 g fresh PSP in yield) were found by HPLC analysis. The PSP extract also contained 17.11 mg mL–1 of protein, 0.44 mg mL–1 of dietary fiber, 2.82 mg mL–1 of reducing sugars, 4.02 ug mL–1 of Se, 54.21 ug mL–1 of Ca and 60.83 ug mL–1 of Mg. Changes in color and stability of the PSP extract, as affected by pH, heat, light and extraction process, were further evaluated. Results indicated that PSP anthocyanins had good stability at pH 2.0-6.0, while the color of PSP extract kept stable during 30 days of storage at 20 °C in dark. Both UV and fluorescent exposure weakened the color stability of PSP extract and UV showed a more drastic effect in comparison. A steaming pretreatment of fresh PSP is beneficial to the color stability.

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Color texture classification is an important step in image segmentation and recognition. The color information is especially important in textures of natural scenes, such as leaves surfaces, terrains models, etc. In this paper, we propose a novel approach based on the fractal dimension for color texture analysis. The proposed approach investigates the complexity in R, G and B color channels to characterize a texture sample. We also propose to study all channels in combination, taking into consideration the correlations between them. Both these approaches use the volumetric version of the Bouligand-Minkowski Fractal Dimension method. The results show a advantage of the proposed method over other color texture analysis methods. (C) 2011 Elsevier Ltd. All rights reserved.

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In this thesis, I study skin lesion detection and its applications to skin cancer diagnosis. A skin lesion detection algorithm is proposed. The proposed algorithm is based color information and threshold. For the proposed algorithm, several color spaces are studied and the detection results are compared. Experimental results show that YUV color space can achieve the best performance. Besides, I develop a distance histogram based threshold selection method and the method is proven to be better than other adaptive threshold selection methods for color detection. Besides the detection algorithms, I also investigate GPU speed-up techniques for skin lesion extraction and the results show that GPU has potential applications in speeding-up skin lesion extraction. Based on the skin lesion detection algorithms proposed, I developed a mobile-based skin cancer diagnosis application. In this application, the user with an iPhone installed with the proposed application can use the iPhone as a diagnosis tool to find the potential skin lesions in a persons' skin and compare the skin lesions detected by the iPhone with the skin lesions stored in a database in a remote server.

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Reflectance spectra collected during ODP Leg 172 were used in concert with solid phase iron chemistry, carbonate content, and organic carbon content measurements to evaluate the agents responsible for setting the color in sediments. Factor analysis has proved a valuable and rapid technique to detect the local and regional primary factors that influence sediment color. On the western North Atlantic drifts, sediment color is the result of primary mineralogy as well as diagenetic changes. Sediment lightness is controlled by the carbonate content while the hue is primarily due to the presence of hematite and Fe2+/Fe3+ changes in clay minerals. Hematite, most likely derived from the Permo-Carboniferous red beds of the Canadian Maritimes, is differentially preserved at various sites due to differences in reductive diagenesis and dilution by other sedimentary components. Various intensities for diagenesis result from changes in organic carbon content, sedimentation rates, and H2S production via anaerobic methane oxidation. Iron monosulfides occur extensively at all high sedimentation sites especially in glacial periods suggesting increased high terrigenous flux and/or increased reactive iron flux in glacials.

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In this paper a new method for image retrieval using high level color semantic features is proposed. It is based on extraction of low level color characteristics and their conversion into high level semantic features using Johannes Itten theory of color, Dempster-Shafer theory of evidence and fuzzy production rules.

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The offered paper deals with the problems of color images preliminary procession. Among these are: interference control (local ones and noise) and extraction of the object from the background on the stage preceding the process of contours extraction. It was considered for a long time that execution of smoothing in segmentation through the boundary extraction is inadmissible, but the described methods and the obtained results evidence about expedience of using the noise control methods.

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The use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classification of images in glaucomatous or not. We obtained results of 93% accuracy

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Automatic video segmentation plays a vital role in sports videos annotation. This paper presents a fully automatic and computationally efficient algorithm for analysis of sports videos. Various methods of automatic shot boundary detection have been proposed to perform automatic video segmentation. These investigations mainly concentrate on detecting fades and dissolves for fast processing of the entire video scene without providing any additional feedback on object relativity within the shots. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos.

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To detect the presence of male DNA in vaginal samples collected from survivors of sexual violence and stored on filter paper. A pilot study was conducted to evaluate 10 vaginal samples spotted on sterile filter paper: 6 collected at random in April 2009 and 4 in October 2010. Time between sexual assault and sample collection was 4-48hours. After drying at room temperature, the samples were placed in a sterile envelope and stored for 2-3years until processing. DNA extraction was confirmed by polymerase chain reaction for human β-globin, and the presence of prostate-specific antigen (PSA) was quantified. The presence of the Y chromosome was detected using primers for sequences in the TSPY (Y7/Y8 and DYS14) and SRY genes. β-Globin was detected in all 10 samples, while 2 samples were positive for PSA. Half of the samples amplified the Y7/Y8 and DYS14 sequences of the TSPY gene and 30% amplified the SRY gene sequence of the Y chromosome. Four male samples and 1 female sample served as controls. Filter-paper spots stored for periods of up to 3years proved adequate for preserving genetic material from vaginal samples collected following sexual violence.