Search results for: color and texture features
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2069

Search results for: color and texture features

1679 Tomato Ripeness Influence on Fruit Quality

Authors: A. Radzevičius, P. Viškelis, R. Karklelienė, J. Viškelis, Č. Bobinas, E. Dambrauskienė andS. Sakalauskienė

Abstract:

Tomato nutrition value, color, flavor of their fruits and products depends mainly on lycopene, β-carotene, ascorbic acid, sugars and their ratio. The two most important carotenoids in fruits of tomato are lycopene, which determined fruits red color, and β- carotene, which accounts for approximately 7% of the tomato carotenoids. Therefore, tomato products and their quality can be well characterized by the content of these elements.Maturity at harvest is very important to composition and quality of tomatoes. This is especially a problem with tomatoes picked green since it is difficult to differentiate between mature and immature-green fruits. Typical and advanced mature-green tomatoes will usually attain a much better flavor than those picked at the immature or partially mature stages.To better understand the synthesis of biochemical compounds, their concentration should be compared not only at the last stage of maturity, but also during all fruit ripening period in different varieties.

Keywords: quality, ripeness, tomato, variety

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1678 A Study of the Variability of Very Low Resolution Characters and the Feasibility of Their Discrimination Using Geometrical Features

Authors: Farshideh Einsele, Rolf Ingold

Abstract:

Current OCR technology does not allow to accurately recognizing small text images, such as those found in web images. Our goal is to investigate new approaches to recognize very low resolution text images containing antialiased character shapes. This paper presents a preliminary study on the variability of such characters and the feasibility to discriminate them by using geometrical features. In a first stage we analyze the distribution of these features. In a second stage we present a study on the discriminative power for recognizing isolated characters, using various rendering methods and font properties. Finally we present interesting results of our evaluation tests leading to our conclusion and future focus.

Keywords: World Wide Web, document analysis, pattern recognition, Optical Character Recognition.

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1677 Effect of Replacement of Unripe Banana Flour for Rice Flour on Physical Properties and Resistant Starch Content of Rice Noodle

Authors: W. Tiboonbun, M. Sungsri-in, A. Moongngarm

Abstract:

This work was conducted to improve the level of resistant starch (RS) in a rice noodle using unripe banana flour and to investigate the effect of substitution of unripe banana flour for rice flour on the physical properties of rice noodle. In order to prepare rice noodles, the unripe banana flour were replaced the rice flour with different degrees of substitutions including 0, 20, 40, 60, 80, and 100%. The results indicated that substitution of unripe banana flour was significantly affected the viscosity properties of noodle flour, color, cooking loss, RS and total starch content of noodle. It was found that the noodle prepared from 100% unripe banana indicated the greatest changes on the viscosity properties and color profiles. It also showed the highest values of cooking loss (2.53%), tensile strength (129.03%), and RS content (13.15%).

Keywords: Banana flour, Rice noodle, Resistant starch, Unripebanana flour

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1676 Performance Analysis of Chrominance Red and Chrominance Blue in JPEG

Authors: Mamta Garg

Abstract:

While compressing text files is useful, compressing still image files is almost a necessity. A typical image takes up much more storage than a typical text message and without compression images would be extremely clumsy to store and distribute. The amount of information required to store pictures on modern computers is quite large in relation to the amount of bandwidth commonly available to transmit them over the Internet and applications. Image compression addresses the problem of reducing the amount of data required to represent a digital image. Performance of any image compression method can be evaluated by measuring the root-mean-square-error & peak signal to noise ratio. The method of image compression that will be analyzed in this paper is based on the lossy JPEG image compression technique, the most popular compression technique for color images. JPEG compression is able to greatly reduce file size with minimal image degradation by throwing away the least “important" information. In JPEG, both color components are downsampled simultaneously, but in this paper we will compare the results when the compression is done by downsampling the single chroma part. In this paper we will demonstrate more compression ratio is achieved when the chrominance blue is downsampled as compared to downsampling the chrominance red in JPEG compression. But the peak signal to noise ratio is more when the chrominance red is downsampled as compared to downsampling the chrominance blue in JPEG compression. In particular we will use the hats.jpg as a demonstration of JPEG compression using low pass filter and demonstrate that the image is compressed with barely any visual differences with both methods.

Keywords: JPEG, Discrete Cosine Transform, Quantization, Color Space Conversion, Image Compression, Peak Signal to Noise Ratio & Compression Ratio.

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1675 Learning to Recognize Faces by Local Feature Design and Selection

Authors: Yanwei Pang, Lei Zhang, Zhengkai Liu

Abstract:

Studies in neuroscience suggest that both global and local feature information are crucial for perception and recognition of faces. It is widely believed that local feature is less sensitive to variations caused by illumination, expression and illumination. In this paper, we target at designing and learning local features for face recognition. We designed three types of local features. They are semi-global feature, local patch feature and tangent shape feature. The designing of semi-global feature aims at taking advantage of global-like feature and meanwhile avoiding suppressing AdaBoost algorithm in boosting weak classifies established from small local patches. The designing of local patch feature targets at automatically selecting discriminative features, and is thus different with traditional ways, in which local patches are usually selected manually to cover the salient facial components. Also, shape feature is considered in this paper for frontal view face recognition. These features are selected and combined under the framework of boosting algorithm and cascade structure. The experimental results demonstrate that the proposed approach outperforms the standard eigenface method and Bayesian method. Moreover, the selected local features and observations in the experiments are enlightening to researches in local feature design in face recognition.

Keywords: Face recognition, local feature, AdaBoost, subspace analysis.

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1674 Estimation and Removal of Chlorophenolic Compounds from Paper Mill Waste Water by Electrochemical Treatment

Authors: R. Sharma, S. Kumar, C. Sharma

Abstract:

A number of toxic chlorophenolic compounds are formed during pulp bleaching. The nature and concentration of these chlorophenolic compounds largely depends upon the amount and nature of bleaching chemicals used. These compounds are highly recalcitrant and difficult to remove but are partially removed by the biochemical treatment processes adopted by the paper industry. Identification and estimation of these chlorophenolic compounds has been carried out in the primary and secondary clarified effluents from the paper mill by GCMS. Twenty-six chorophenolic compounds have been identified and estimated in paper mill waste waters. Electrochemical treatment is an efficient method for oxidation of pollutants and has successfully been used to treat textile and oil waste water. Electrochemical treatment using less expensive anode material, stainless steel electrodes has been tried to study their removal. The electrochemical assembly comprised a DC power supply, a magnetic stirrer and stainless steel (316 L) electrode. The optimization of operating conditions has been carried out and treatment has been performed under optimized treatment conditions. Results indicate that 68.7% and 83.8% of cholorphenolic compounds are removed during 2 h of electrochemical treatment from primary and secondary clarified effluent respectively. Further, there is a reduction of 65.1, 60 and 92.6% of COD, AOX and color, respectively for primary clarified and 83.8%, 75.9% and 96.8% of COD, AOX and color, respectively for secondary clarified effluent. EC treatment has also been found to increase significantly the biodegradability index of wastewater because of conversion of non- biodegradable fraction into biodegradable fraction. Thus, electrochemical treatment is an efficient method for the degradation of cholorophenolic compounds, removal of color, AOX and other recalcitrant organic matter present in paper mill waste water.

Keywords: Chlorophenolics, effluent, electrochemical treatment, wastewater.

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1673 Tracking Objects in Color Image Sequences: Application to Football Images

Authors: Mourad Moussa, Ali Douik, Hassani Messaoud

Abstract:

In this paper, we present a comparative study between two computer vision systems for objects recognition and tracking, these algorithms describe two different approach based on regions constituted by a set of pixels which parameterized objects in shot sequences. For the image segmentation and objects detection, the FCM technique is used, the overlapping between cluster's distribution is minimized by the use of suitable color space (other that the RGB one). The first technique takes into account a priori probabilities governing the computation of various clusters to track objects. A Parzen kernel method is described and allows identifying the players in each frame, we also show the importance of standard deviation value research of the Gaussian probability density function. Region matching is carried out by an algorithm that operates on the Mahalanobis distance between region descriptors in two subsequent frames and uses singular value decomposition to compute a set of correspondences satisfying both the principle of proximity and the principle of exclusion.

Keywords: Image segmentation, objects tracking, Parzen window, singular value decomposition, target recognition.

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1672 Identification of Healthy and BSR-Infected Oil Palm Trees Using Color Indices

Authors: Siti Khairunniza-Bejo, Yusnida Yusoff, Nik Salwani Nik Yusoff, Idris Abu Seman, Mohamad Izzuddin Anuar

Abstract:

Most of the oil palm plantations have been threatened by Basal Stem Rot (BSR) disease which causes serious economic impact. This study was conducted to identify the healthy and BSRinfected oil palm tree using thirteen color indices. Multispectral and thermal camera was used to capture 216 images of the leaves taken from frond number 1, 9 and 17. Indices of normalized difference vegetation index (NDVI), red (R), green (G), blue (B), near infrared (NIR), green – blue (GB), green/blue (G/B), green – red (GR), green/red (G/R), hue (H), saturation (S), intensity (I) and thermal index (T) were used. From this study, it can be concluded that G index taken from frond number 9 is the best index to differentiate between the healthy and BSR-infected oil palm trees. It not only gave high value of correlation coefficient (R=-0.962), but also high value of separation between healthy and BSR-infected oil palm tree. Furthermore, power and S model developed using G index gave the highest R2 value which is 0.985.

Keywords: Oil palm, image processing, disease, leaves.

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1671 Active Segment Selection Method in EEG Classification Using Fractal Features

Authors: Samira Vafaye Eslahi

Abstract:

BCI (Brain Computer Interface) is a communication machine that translates brain massages to computer commands. These machines with the help of computer programs can recognize the tasks that are imagined. Feature extraction is an important stage of the process in EEG classification that can effect in accuracy and the computation time of processing the signals. In this study we process the signal in three steps of active segment selection, fractal feature extraction, and classification. One of the great challenges in BCI applications is to improve classification accuracy and computation time together. In this paper, we have used student’s 2D sample t-statistics on continuous wavelet transforms for active segment selection to reduce the computation time. In the next level, the features are extracted from some famous fractal dimension estimation of the signal. These fractal features are Katz and Higuchi. In the classification stage we used ANFIS (Adaptive Neuro-Fuzzy Inference System) classifier, FKNN (Fuzzy K-Nearest Neighbors), LDA (Linear Discriminate Analysis), and SVM (Support Vector Machines). We resulted that active segment selection method would reduce the computation time and Fractal dimension features with ANFIS analysis on selected active segments is the best among investigated methods in EEG classification.

Keywords: EEG, Student’s t- statistics, BCI, Fractal Features, ANFIS, FKNN.

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1670 Speaker Identification using Neural Networks

Authors: R.V Pawar, P.P.Kajave, S.N.Mali

Abstract:

The speech signal conveys information about the identity of the speaker. The area of speaker identification is concerned with extracting the identity of the person speaking the utterance. As speech interaction with computers becomes more pervasive in activities such as the telephone, financial transactions and information retrieval from speech databases, the utility of automatically identifying a speaker is based solely on vocal characteristic. This paper emphasizes on text dependent speaker identification, which deals with detecting a particular speaker from a known population. The system prompts the user to provide speech utterance. System identifies the user by comparing the codebook of speech utterance with those of the stored in the database and lists, which contain the most likely speakers, could have given that speech utterance. The speech signal is recorded for N speakers further the features are extracted. Feature extraction is done by means of LPC coefficients, calculating AMDF, and DFT. The neural network is trained by applying these features as input parameters. The features are stored in templates for further comparison. The features for the speaker who has to be identified are extracted and compared with the stored templates using Back Propogation Algorithm. Here, the trained network corresponds to the output; the input is the extracted features of the speaker to be identified. The network does the weight adjustment and the best match is found to identify the speaker. The number of epochs required to get the target decides the network performance.

Keywords: Average Mean Distance function, Backpropogation, Linear Predictive Coding, MultilayeredPerceptron,

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1669 Diagnosis of the Abdominal Aorta Aneurysm in Magnetic Resonance Imaging Images

Authors: W. Kultangwattana, K. Somkantha, P. Phuangsuwan

Abstract:

This paper presents a technique for diagnosis of the abdominal aorta aneurysm in magnetic resonance imaging (MRI) images. First, our technique is designed to segment the aorta image in MRI images. This is a required step to determine the volume of aorta image which is the important step for diagnosis of the abdominal aorta aneurysm. Our proposed technique can detect the volume of aorta in MRI images using a new external energy for snakes model. The new external energy for snakes model is calculated from Law-s texture. The new external energy can increase the capture range of snakes model efficiently more than the old external energy of snakes models. Second, our technique is designed to diagnose the abdominal aorta aneurysm by Bayesian classifier which is classification models based on statistical theory. The feature for data classification of abdominal aorta aneurysm was derived from the contour of aorta images which was a result from segmenting of our snakes model, i.e., area, perimeter and compactness. We also compare the proposed technique with the traditional snakes model. In our experiment results, 30 images are trained, 20 images are tested and compared with expert opinion. The experimental results show that our technique is able to provide more accurate results than 95%.

Keywords: Adbominal Aorta Aneurysm, Bayesian Classifier, Snakes Model, Texture Feature.

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1668 The Costume Design by the Inspiration of The Figurehead of Thai Royal Barges

Authors: Taechit Cheuypoung

Abstract:

The purpose of this research was to design costume by the inspiration from the configurations, colors and decorations of Thai Royal Barges. The researcher investigated the bibliographies and the important of the Thai Royal Water-Course Procession, configurations and decoration techniques of four Royal Barges history. Furthermore, the researcher combined the contemporary architecture which became part of the four costumes with four patterns in this research. The four costumes designed by applied the physical configuration of the Royal Barge with the fold techniques which create the geometry pattern that are part of the Royal Barge-s decoration and contemporary architecture. Therefore, the researcher united each identity color of the barges with each costume composed with the original patterns by adjusted new layout and resized. Lastly, the new attractive patterns appeared. Nevertheless, the beauty of Thai traditional still remain by using Thai painting figure with black and white color which are the prevalent colors for the contemporary architectures.

Keywords: Costume Design, Figurehead, Thai Royal Barges.

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1667 Life Experiences are Important Factors of Making Stronger SOC (Sense of Coherence) on the Workers in Tsukuba Research Park City (TRPC)

Authors: Shinichiro Sasahara, Yusuke Tomotsune, Yuichi Ohi, Shun Suzuki, Akihiro Seki, Junko Sakano, Yoshihiko Yamazaki, Ichiyo Matsuzaki

Abstract:

Via a large scale cross-sectional study among Japanese white color workers, the authors aimed to elucidate: (1) the distributions of Sense of Coherence (SOC), which reflect stress coping abilities, (2) the distributions of Life experience; (3) and the association between SOC and Life experience. Anonymous self-administered questionnaires were sent to 15,891 in 2001 and 21,922 in 2011 employees at educational and research institutions in Tsukuba Research Park City. A total of 5,868 (36.9%) and 9,528 (43.5%) respectively workers completed and returned the questionnaire; 5,715 and 9,515 respectively workers without missing data were analyzed. SOC scale scores differed by gender, age, and other demographic features in both study years. Among the life experiences, workers who have got over parenting or management position were higher SOC scale scores adjusted by gender and age. The life experiences that workers have got over could develop their stronger SOC in their life course.

Keywords: field study, life experience, mental health, SOC (sense of coherence)

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1666 The Effect of Nano-Silver Packaging on Quality Maintenance of Fresh Strawberry

Authors: Naser Valipour Motlagh, Majid Aliabadi, Elnaz Rahmani, Samira Ghorbanpour

Abstract:

Strawberry is one of the most favored fruits all along the world. But due to its vulnerability to microbial contamination and short life storage, there are lots of problems in industrial production and transportation of this fruit. Therefore, lots of ideas have tried to increase the storage life of strawberries especially through proper packaging. This paper works on efficient packaging as well. The primary material used is produced through simple mixing of low-density polyethylene (LDPE) and silver nanoparticles in different weight fractions of 0.5 and 1% in presence of dicumyl peroxide as a cross-linking agent. Final packages were made in a twin-screw extruder. Then, their effect on the quality maintenance of strawberry is evaluated. The SEM images of nano-silver packages show the distribution of silver nanoparticles in the packages. Total bacteria count, mold, yeast and E. coli are measured for microbial evaluation of all samples. Texture, color, appearance, odor, taste and total acceptance of various samples are evaluated by trained panelists and based on 9-point hedonic scale method. The results show a decrease in total bacteria count and mold in nano-silver packages compared to the samples packed in polyethylene packages for the same storage time. The optimum concentration of silver nanoparticles for the lowest bacteria count and mold is predicted to be around 0.5% which has attained the most acceptance from the panelist as well. Moreover, organoleptic properties of strawberry are preserved for a longer period in nano-silver packages. It can be concluded that using nano-silver particles in strawberry packages has improved the storage life and quality maintenance of the fruit.

Keywords: Antimicrobial properties, polyethylene, silver nanoparticles, strawberry.

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1665 Morpho-Anatomical and Ecological Studies on Endemic of Fritillaria oranensis Pomel. from the Mounts of Tessala (Western Algeria)

Authors: A. Bouzid, R. Chadli

Abstract:

Fritillaria oranensis (Liliaceae) was described in 1874 by pomel from Algeria. Plant samples have been collected from the mount of Tessala (Sidi-Bel-Abbes). The morphological features of various organs of the plant are described in detail. In the morphological part of the study, features of various organs of the plants such as stem and leaf were determined and illustrated. Ecological studies provide information about the physical and chemical structure of soil types in Tessala Mountain. The aim of this original investigation is to put forth ecological and anatomical features of these species for the first time, but at the same time given detailed account of the morphological characteristics of the stem and leaf of Fritillaria oranensis.

Keywords: Anatomy, ecology, Liliaceae, morphology, Fritillaria oranensis Pomel.

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1664 Player Number Localization and Recognition in Soccer Video using HSV Color Space and Internal Contours

Authors: Matko Šaric, Hrvoje Dujmic, Vladan Papic, Nikola Rožic

Abstract:

Detection of player identity is challenging task in sport video content analysis. In case of soccer video player number recognition is effective and precise solution. Jersey numbers can be considered as scene text and difficulties in localization and recognition appear due to variations in orientation, size, illumination, motion etc. This paper proposed new method for player number localization and recognition. By observing hue, saturation and value for 50 different jersey examples we noticed that most often combination of low and high saturated pixels is used to separate number and jersey region. Image segmentation method based on this observation is introduced. Then, novel method for player number localization based on internal contours is proposed. False number candidates are filtered using area and aspect ratio. Before OCR processing extracted numbers are enhanced using image smoothing and rotation normalization.

Keywords: player number, soccer video, HSV color space

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1663 Extend of Self-Life of Potato Round Slices with Edible Coating, Green Tea and Ascorbic Acid

Authors: A. Spanou, P. Giannouli

Abstract:

The effects of coatings based on sodium alginate (S.A) and carboxyl methyl cellulose (CMC) on the color and moisture characteristics of potato round slices were investigated. It is the first time that this combination of polysaccharides is used as edible coating which alone had the best performance as inhibitor of potato color discoloration during the storage of 15 days at 4oC. When ascorbic acid (AA) and green tea (GT) were added in the above edible coating its effects on potato round slices changed. The mixtures of sodium alginate and carboxyl methyl cellulose with ascorbic acid or with green tea behave as a potential moisture barrier, resulting to the extent of potato samples self–life. These data suggests that both GT and AA are potential inhibitors of dehydration in potatoes and not only natural antioxidants.

Keywords: Ascorbic acid, edible coating, green tea, moisture barrier.

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1662 Uncertainty Multiple Criteria Decision Making Analysis for Stealth Combat Aircraft Selection

Authors: C. Ardil

Abstract:

Fuzzy set theory and its extensions (intuitionistic fuzzy sets, picture fuzzy sets, and neutrosophic sets) have been widely used to address imprecision and uncertainty in complex decision-making. However, they may struggle with inherent indeterminacy and inconsistency in real-world situations. This study introduces uncertainty sets as a promising alternative, offering a structured framework for incorporating both types of uncertainty into decision-making processes.This work explores the theoretical foundations and applications of uncertainty sets. A novel decision-making algorithm based on uncertainty set-based proximity measures is developed and demonstrated through a practical application: selecting the most suitable stealth combat aircraft.

The results highlight the effectiveness of uncertainty sets in ranking alternatives under uncertainty. Uncertainty sets offer several advantages, including structured uncertainty representation, robust ranking mechanisms, and enhanced decision-making capabilities due to their ability to account for ambiguity.Future research directions are also outlined, including comparative analysis with existing MCDM methods under uncertainty, sensitivity analysis to assess the robustness of rankings,and broader application to various MCDM problems with diverse complexities. By exploring these avenues, uncertainty sets can be further established as a valuable tool for navigating uncertainty in complex decision-making scenarios.

Keywords: Uncertainty set, stealth combat aircraft selection multiple criteria decision-making analysis, MCDM, uncertainty proximity analysis

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1661 Improving Worm Detection with Artificial Neural Networks through Feature Selection and Temporal Analysis Techniques

Authors: Dima Stopel, Zvi Boger, Robert Moskovitch, Yuval Shahar, Yuval Elovici

Abstract:

Computer worm detection is commonly performed by antivirus software tools that rely on prior explicit knowledge of the worm-s code (detection based on code signatures). We present an approach for detection of the presence of computer worms based on Artificial Neural Networks (ANN) using the computer's behavioral measures. Identification of significant features, which describe the activity of a worm within a host, is commonly acquired from security experts. We suggest acquiring these features by applying feature selection methods. We compare three different feature selection techniques for the dimensionality reduction and identification of the most prominent features to capture efficiently the computer behavior in the context of worm activity. Additionally, we explore three different temporal representation techniques for the most prominent features. In order to evaluate the different techniques, several computers were infected with five different worms and 323 different features of the infected computers were measured. We evaluated each technique by preprocessing the dataset according to each one and training the ANN model with the preprocessed data. We then evaluated the ability of the model to detect the presence of a new computer worm, in particular, during heavy user activity on the infected computers.

Keywords: Artificial Neural Networks, Feature Selection, Temporal Analysis, Worm Detection.

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1660 The Laser Line Detection for Autonomous Mapping Based on Color Segmentation

Authors: Pavel Chmelar, Martin Dobrovolny

Abstract:

Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: Automatic mapping, color segmentation, component labeling, distance measurement, laser line detection, vector map.

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1659 Combined Feature Based Hyperspectral Image Classification Technique Using Support Vector Machines

Authors: Mrs.K.Kavitha, S.Arivazhagan

Abstract:

A spatial classification technique incorporating a State of Art Feature Extraction algorithm is proposed in this paper for classifying a heterogeneous classes present in hyper spectral images. The classification accuracy can be improved if and only if both the feature extraction and classifier selection are proper. As the classes in the hyper spectral images are assumed to have different textures, textural classification is entertained. Run Length feature extraction is entailed along with the Principal Components and Independent Components. A Hyperspectral Image of Indiana Site taken by AVIRIS is inducted for the experiment. Among the original 220 bands, a subset of 120 bands is selected. Gray Level Run Length Matrix (GLRLM) is calculated for the selected forty bands. From GLRLMs the Run Length features for individual pixels are calculated. The Principle Components are calculated for other forty bands. Independent Components are calculated for next forty bands. As Principal & Independent Components have the ability to represent the textural content of pixels, they are treated as features. The summation of Run Length features, Principal Components, and Independent Components forms the Combined Features which are used for classification. SVM with Binary Hierarchical Tree is used to classify the hyper spectral image. Results are validated with ground truth and accuracies are calculated.

Keywords: Multi-class, Run Length features, PCA, ICA, classification and Support Vector Machines.

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1658 A Proposed Hybrid Approach for Feature Selection in Text Document Categorization

Authors: M. F. Zaiyadi, B. Baharudin

Abstract:

Text document categorization involves large amount of data or features. The high dimensionality of features is a troublesome and can affect the performance of the classification. Therefore, feature selection is strongly considered as one of the crucial part in text document categorization. Selecting the best features to represent documents can reduce the dimensionality of feature space hence increase the performance. There were many approaches has been implemented by various researchers to overcome this problem. This paper proposed a novel hybrid approach for feature selection in text document categorization based on Ant Colony Optimization (ACO) and Information Gain (IG). We also presented state-of-the-art algorithms by several other researchers.

Keywords: Ant colony optimization, feature selection, information gain, text categorization, text representation.

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1657 Features of Soil Formation in the North of Western Siberia in Cryogenic Conditions

Authors: Tatiana V. Raudina, Sergey P. Kulizhskiy

Abstract:

A large part of Russia is located in permafrost areas. These areas are widely used because there are concentrated valuable natural resources. Therefore to explore of cryosols it is important due to the significant increase of anthropogenic stress as well as the problem of global climate change. In the north of Western Siberia permafrost phenomena is widespread. Permafrost as a factor of soil formation and cryogenesis as a process have a great impact on the soil formation of these areas. Based on the research results of permafrost-affected soils tundra landscapes formed in the central part of the Tazovskiy Peninsula in cryogenic conditions, data were obtained which characterize the morphological features of soils. The specificity of soil cover distribution and manifestation of soil-forming processes within the study area are noted. Permafrost features such as frost cracking, cryoturbation, thixotropy, movement of humus are formed. The formation of these features is increased with the development of the territory. As a consequence, there is a change in the components of the environment and the destruction of the soil cover.

Keywords: Gleyed and nongleyed soils, permafrost, soil cryogenesis (pedocryogenesis), soil-forming macroprocesses.

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1656 Persian Pistachio Nut (Pistacia vera L.) Dehydration in Natural and Industrial Conditions

Authors: Hamid Tavakolipour, Mohsen Mokhtarian, Ahmad Kalbasi Ashtari

Abstract:

In this study, the effect of various drying methods (sun drying, shade drying and industrial drying) on final moisture content, shell splitting degree, shrinkage and color change were studied. Sun drying resulted higher degree of pistachio nuts shell splitting on pistachio nuts relative other drying methods. The ANOVA results showed that the different drying methods did not significantly effects on color change of dried pistachio nut. The results illustrated that pistachio nut dried by industrial drying had the lowest moisture content. After the end of drying process, initially, the experimental drying data were fitted with five famous drying models namely Newton, Page, Silva et al., Peleg and Henderson and Pabis. The results indicated that Peleg and Page models gave better results compared with other models to monitor the moisture ratio’s pistachio nut in industrial drying and open sun (or shade drying) methods, respectively.

Keywords: Industrial drying, Modeling, Pistachio, quality properties, Traditional drying.

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1655 3D Dense Correspondence for 3D Dense Morphable Face Shape Model

Authors: Tae in Seol, Sun-Tae Chung, Seongwon Cho

Abstract:

Realistic 3D face model is desired in various applications such as face recognition, games, avatars, animations, and etc. Construction of 3D face model is composed of 1) building a face shape model and 2) rendering the face shape model. Thus, building a realistic 3D face shape model is an essential step for realistic 3D face model. Recently, 3D morphable model is successfully introduced to deal with the various human face shapes. 3D dense correspondence problem should be precedently resolved for constructing a realistic 3D dense morphable face shape model. Several approaches to 3D dense correspondence problem in 3D face modeling have been proposed previously, and among them optical flow based algorithms and TPS (Thin Plate Spline) based algorithms are representative. Optical flow based algorithms require texture information of faces, which is sensitive to variation of illumination. In TPS based algorithms proposed so far, TPS process is performed on the 2D projection representation in cylindrical coordinates of the 3D face data, not directly on the 3D face data and thus errors due to distortion in data during 2D TPS process may be inevitable. In this paper, we propose a new 3D dense correspondence algorithm for 3D dense morphable face shape modeling. The proposed algorithm does not need texture information and applies TPS directly on 3D face data. Through construction procedures, it is observed that the proposed algorithm constructs realistic 3D face morphable model reliably and fast.

Keywords: 3D Dense Correspondence, 3D Morphable Face Shape Model, 3D Face Modeling.

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1654 Optical Properties of WO3-NiO Complementary Electrochromic Devices

Authors: Chih-Ming Wang, Chih-Yu Wen, Ying-Chung Chen, Chun-Chieh Wang, Chien-Chung Hsu, Jui-Yang Chang, Jyun-Min Lin

Abstract:

In this study, we developed a complementary electrochromic device consisting of WO3 and NiO films fabricated by rf-magnetron sputtered. The electrochromic properties of WO3 and NiO films were investigated using cyclic voltammograms (CV), performed on WO3 and NiO films immersed in an electrolyte of 1 M LiClO4 in propylene carbonate (PC). Optical and electrochemical of the films, as a function of coloration–bleaching cycle, were characterized using an UV-Vis-NIR spectrophotometer and cyclic voltammetry (CV). After investigating the properties of WO3 film, NiO film, and complementary electrochromic devices, we concluded that this device provides good reversibility, low power consumption of -2.5 V in color state, high variation of transmittance of 58.96%, changes in optical density of 0.81 and good memory effect under open-circuit conditions. In addition, electrochromic component penetration rate can be retained below 20% within 24h, showing preferred memory features; however, component coloring and bleaching response time are about 33s.

Keywords: Complementary electrochromic device, Rf-magnetron sputtered, Transmittance, Memory effect, Optical density change

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1653 Application of Genetic Algorithms to Feature Subset Selection in a Farsi OCR

Authors: M. Soryani, N. Rafat

Abstract:

Dealing with hundreds of features in character recognition systems is not unusual. This large number of features leads to the increase of computational workload of recognition process. There have been many methods which try to remove unnecessary or redundant features and reduce feature dimensionality. Besides because of the characteristics of Farsi scripts, it-s not possible to apply other languages algorithms to Farsi directly. In this paper some methods for feature subset selection using genetic algorithms are applied on a Farsi optical character recognition (OCR) system. Experimental results show that application of genetic algorithms (GA) to feature subset selection in a Farsi OCR results in lower computational complexity and enhanced recognition rate.

Keywords: Feature Subset Selection, Genetic Algorithms, Optical Character Recognition.

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1652 Unequal Error Protection of Facial Features for Personal ID Images Coding

Authors: T. Hirner, J. Polec

Abstract:

This paper presents an approach for an unequal error protection of facial features of personal ID images coding. We consider unequal error protection (UEP) strategies for the efficient progressive transmission of embedded image codes over noisy channels. This new method is based on the progressive image compression embedded zerotree wavelet (EZW) algorithm and UEP technique with defined region of interest (ROI). In this case is ROI equal facial features within personal ID image. ROI technique is important in applications with different parts of importance. In ROI coding, a chosen ROI is encoded with higher quality than the background (BG). Unequal error protection of image is provided by different coding techniques and encoding LL band separately. In our proposed method, image is divided into two parts (ROI, BG) that consist of more important bytes (MIB) and less important bytes (LIB). The proposed unequal error protection of image transmission has shown to be more appropriate to low bit rate applications, producing better quality output for ROI of the compresses image. The experimental results verify effectiveness of the design. The results of our method demonstrate the comparison of the UEP of image transmission with defined ROI with facial features and the equal error protection (EEP) over additive white gaussian noise (AWGN) channel.

Keywords: Embedded zerotree wavelet (EZW), equal error protection (EEP), facial features, personal ID images, region of interest (ROI), unequal error protection (UEP)

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1651 Face Recognition Using Discrete Orthogonal Hahn Moments

Authors: Fatima Akhmedova, Simon Liao

Abstract:

One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, nonredundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: Face Recognition, Hahn moments, Recognition-by-parts, Time-lapse.

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1650 Effect of Dietary Linseed Oil Soap on Lamb Meat

Authors: E. Zsédely, A. Király, Cs. Szabó., K. Németh, O. Dóka, J. Schmidt

Abstract:

Theexperiment was carried out with 2x5 male Merino lambs raised under intensive conditions to investigate the effect of dietary calcium soap of linseed oil on the color and fatty acid composition of longissimusdorsi muscle. Control lambs fed a basal diet and the experimental lambs consumed a diet supplemented with 3% calcium soap of linseed oil. The color values (L*, a*, b* a*/b* and chroma) were not influenced by dietary treatment. The MUFA proportion reduced, SFA and PUFA content did not alter. As expected, the linolenic (C18:3 n3) and thusthe n-3 content significantly improved by linseed supplement (0.47 and 0.81; 0.78 and 1.16 in control and in experimental samples, respectively). Other n-3 and n-6 fatty acids had similar valuestocontrol samples. The n- 6/n-3 ratio was significantly narrower in the experimental group (6.31 vs. 9.38) but the P/S ratio did not differ betweenthe two groups.In conclusion calcium soap of linseed oil seems to be a suitable supplement form of n-3 fatty acids to improve the nutritive value of lamb meat.

Keywords: calcium soap, fatty acid, lamb meat, linseed

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