Search results for: color image.

Authors: K.V. Sridhar, Varun Gunnala, K.S.R Krishna Prasad

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In this paper three basic approaches and different methods under each of them for extracting region of interest (ROI) from stationary images are explored. The results obtained for each of the proposed methods are shown, and it is demonstrated where each method outperforms the other. Two main problems in ROI extraction: the channel selection problem and the saliency reversal problem are discussed and how best these two are addressed by various methods is also seen. The basic approaches are 1) Saliency based approach 2) Wavelet based approach 3) Clustering based approach. The saliency approach performs well on images containing objects of high saturation and brightness. The wavelet based approach performs well on natural scene images that contain regions of distinct textures. The mean shift clustering approach partitions the image into regions according to the density distribution of pixel intensities. The experimental results of various methodologies show that each technique performs at different acceptable levels for various types of images.

Keywords: clustering, ROI, saliency, wavelets.

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Authors: Viet Dzung Nguyen, Duc Thuan Nguyen, Tien Dzung Nguyen, Van Thanh Pham

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Mammography is the most effective procedure for an early diagnosis of the breast cancer. Nowadays, people are trying to find a way or method to support as much as possible to the radiologists in diagnosis process. The most popular way is now being developed is using Computer-Aided Detection (CAD) system to process the digital mammograms and prompt the suspicious region to radiologist. In this paper, an automated CAD system for detection and classification of massive lesions in mammographic images is presented. The system consists of three processing steps: Regions-Of- Interest detection, feature extraction and classification. Our CAD system was evaluated on Mini-MIAS database consisting 322 digitalized mammograms. The CAD system-s performance is evaluated using Receiver Operating Characteristics (ROC) and Freeresponse ROC (FROC) curves. The archived results are 3.47 false positives per image (FPpI) and sensitivity of 85%.

Keywords: classification, computer-aided detection, featureextraction, mass detection.

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Authors: Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia

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The use of foot recognition can be applied in many medical fields such as the gait pattern analysis and the knee exercises of patients in rehabilitation. Generally, a camera-based foot recognition system is intended to capture a patient image in a controlled room and background to recognize the foot in the limited views. However, this system can be inconvenient to monitor the knee exercises at home. In order to overcome these problems, this paper proposes to use the deep learning method using Convolutional Neural Networks (CNNs) for foot recognition. The results are compared with the traditional classification method using LBP and HOG features with kNN and SVM classifiers. According to the results, deep learning method provides better accuracy but with higher complexity to recognize the foot images from online databases than the traditional classification method.

Keywords: Convolutional neural networks, deep learning, foot recognition, knee rehabilitation.

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Authors: M. Hassan, I. Osman, M. Yahia

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This Paper proposes a new facial feature extraction approach, Wash-Hadamard Transform (WHT). This approach is based on correlation between local pixels of the face image. Its primary advantage is the simplicity of its computation. The paper compares the proposed approach, WHT, which was traditionally used in data compression with two other known approaches: the Principal Component Analysis (PCA) and the Discrete Cosine Transform (DCT) using the face database of Olivetti Research Laboratory (ORL). In spite of its simple computation, the proposed algorithm (WHT) gave very close results to those obtained by the PCA and DCT. This paper initiates the research into WHT and the family of frequency transforms and examines their suitability for feature extraction in face recognition applications.

Keywords: Face Recognition, Facial Feature Extraction, Principal Component Analysis, and Discrete Cosine Transform, Wash-Hadamard Transform.

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Authors: Illyani Ibrahim, Azizan Abu Samah, Rosmadi Fauzi

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Land surface temperature (LST) is an important parameter to study in urban climate. The understanding of the influence of biophysical factors could improve the establishment of modeling urban thermal landscape. It is well established that climate hold a great influence on the urban landscape. However, it has been recognize that climate has a low priority in urban planning process, due to the complex nature of its influence. This study will focus on the relatively cloud free Landsat Thematic Mapper image of the study area, acquired on the 2nd March 2006. Correlation analyses were conducted to identify the relationship of LST to the biophysical factors; vegetation indices, impervious surface, and albedo to investigate the variation of LST. We suggest that the results can be considered by the stackholders during decision-making process to create a cooler and comfortable environment in the urban landscape for city dwellers.

Keywords: Biophysical factors, land surface temperature, urban planning.

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Authors: Anayochukwu Leonard Okoli

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The nexus between language and culture is so intertwined and very significant that language is largely seen as a vehicle for cultural transmission. Culture itself refers to the aggregate belief system of a people, embellishing its corporate national image or brand. If we conceive national rebranding as a campaign to rekindle the patriotic flame in the consciousness of a people towards its sociocultural imperatives and values, then, Nigerian indigenous linguistic flame has not been ignited. Consequently, the paper contends that the current national rebranding policy remains a myth in the confines of the elitists' intellectual squabble. It however recommends that the use of our indigenous languages should be supported by adequate legislation and also propagated by Nollywood in order to revamp and sustain the people’s interest in their local languages. Finally, the use of the indigenous Nigerian languages demonstrates patriotism, an important ingredient for actualizing a genuine national rebranding.

Keywords: Appraisal, Indigenous Languages, Policy, Rebranding.

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Authors: Azwadi Ali

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The survival of publicly listed companies largely depends on their stocks being liquidly traded. This goal can be achieved when new investors are attracted to invest on companies- stocks. Among different groups of investors, individual investors are generally less able to objectively evaluate companies- risks and returns, and tend to be emotionally biased in their investing decisions. Therefore their decisions may be formed as a result of perceived risks and returns, and influenced by companies- images. This study finds that perceived risk, perceived returns and trust directly affect individual investors- trading decisions while attitude towards brand partially mediates the relationships. This finding suggests that, in courting individual investors, companies still need to perform financially while building a good image can result in their stocks being accepted quicker than the stocks of good performing companies with hidden images.

Keywords: Behavioral Finance, Investment, Attitude towardsBrand, Partial Least Squares

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Authors: Hamid Reza Boveiri

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In this paper, a new proposed system for Persian printed numeral characters recognition with emphasis on representation and recognition stages is introduced. For the first time, in Persian optical character recognition, geometrical central moments as character image descriptor and fuzzy min-max neural network for Persian numeral character recognition has been used. Set of different experiments on binary images of regular, translated, rotated and scaled Persian numeral characters has been done and variety of results has been presented. The best result was 99.16% correct recognition demonstrating geometrical central moments and fuzzy min-max neural network are adequate for Persian printed numeral character recognition.

Keywords: Fuzzy min-max neural network, geometrical centralmoments, optical character recognition, Persian digits recognition, Persian printed numeral characters recognition.

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Authors: Yu-Shuai Chen , Chien-Ching Chiu , Chung-Hsin Huang, Chien-Hung Chen

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The bit error rate (BER) performance for ultra-wide band (UWB) indoor communication with impact of metallic furniture is investigated. The impulse responses of different indoor environments for any transmitter and receiver location are computed by shooting and bouncing ray/image and inverse Fourier transform techniques. By using the impulse responses of these multipath channels, the BER performance for binary pulse amplitude modulation (BPAM) impulse radio UWB communication system are calculated. Numerical results have shown that the multi-path effect by the metallic cabinets is an important factor for BER performance. Also the outage probability for the UWB multipath environment with metallic cabinets is more serious (about 18%) than with wooden cabinets. Finally, it is worth noting that in these cases the present work provides not only comparative information but also quantitative information on the performance reduction.

Keywords: UWB, multipath, outage probability.

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Authors: U. Bottigli, M.Carpinelli, P.L. Fiori, B. Golosio, A. Marras, G. L. Masala, P. Oliva

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The counting process of cell colonies is always a long and laborious process that is dependent on the judgment and ability of the operator. The judgment of the operator in counting can vary in relation to fatigue. Moreover, since this activity is time consuming it can limit the usable number of dishes for each experiment. For these purposes, it is necessary that an automatic system of cell colony counting is used. This article introduces a new automatic system of counting based on the elaboration of the digital images of cellular colonies grown on petri dishes. This system is mainly based on the algorithms of region-growing for the recognition of the regions of interest (ROI) in the image and a Sanger neural net for the characterization of such regions. The better final classification is supplied from a Feed-Forward Neural Net (FF-NN) and confronted with the K-Nearest Neighbour (K-NN) and a Linear Discriminative Function (LDF). The preliminary results are shown.

Keywords: Automatic cell counting, neural network, region growing, Sanger net.

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Authors: Jonathan N. Nayga, Emelita B. Valdez, Mila R. Andres, Beulah B. Estrada, Emelina A. Lopez, Rogelio B. Tamayo, Aubrey Joy M. Balbin

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Goat production is one of the activities included in integrated farming in the Philippines. Goats are raised for its meat and regardless of breed the animal is slaughtered for this purpose. In order to document the carcass yield of different goats slaughtered, five (5) different breeds of goats to include Purebred Boer and Anglo-nubian, Crossbred Boer and Anglo-nubian and Philippine Native goat were used in the study. Data on slaughter parameters, carcass characteristics, and sensory evaluation were gathered and analyzed using Complete Random Design (CRD) at 5% level of significance and the results of carcass conformation were assessed descriptively. Results showed that slaughter data such as slaughter/live weight, hot and chilled carcass weights, dressing percentage and percentage drip loss were significantly different (P>0.05) among breeds. On carcass and meat characteristics, pure breed and upgraded Boer were found to be moderately muscular while Native goat was rated as thin muscular. The color of the carcass also revealed that Purebred and crossbred Boer were described dark red, while Native goat was noted to be slightly pale. On sensory evaluation, the results indicated that there was no significant difference (P>0.05) among breeds evaluated. It is therefore concluded that purebred goat has heavier carcass, while both purebred Boer and upgrade are rated slightly muscular. It is further confirms that regardless of breed, goat will have the same sensory characteristics. Thus, it is recommended to slaughter heavier goats to obtain more carcasses with better conformation and quality.

Keywords: Carcass quality, goat, sensory evaluation, slaughter.

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Authors: Francisco Bulnes

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Through the Fukaya conjecture and the wrapped Floer cohomology, the correspondences between paths in a loop space and states of a wrapping space of states in a Hamiltonian space (the ramification of field in this case is the connection to the operator that goes from TM to T*M) are demonstrated where these last states are corresponding to bosonic extensions of a spectrum of the space-time or direct image of the functor Spec, on space-time. This establishes a distinguished diffeomorphism defined by the mapping from the corresponding loops space to wrapping category of the Floer cohomology complex which furthermore relates in certain proportion D-branes (certain D-modules) with strings. This also gives to place to certain conjecture that establishes equivalences between moduli spaces that can be consigned in a moduli identity taking as space-time the Hitchin moduli space on G, whose dual can be expressed by a factor of a bosonic moduli spaces.

Keywords: Floer cohomology, Fukaya conjecture, Lagrangian submanifolds, spectrum of ring, topological quantum diffeomorphisms.

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Authors: Sungwon Jo

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Ceramics comprise the largest proportion of Korea-s cultural heritage currently preserved (Cited from “The Beauty of Old Ceramics of Korea" written by Yoon Yong-iee). Thus, this researcher conducted this investigation in an attempt to gain insight into Korea-s past culture and the lost period of the colonial period and the Korean War by looking into the ceramics. Korea, China and Japan are part of the similar cultural bloc within the East Asian region. Their porcelains manifest distinctive characteristics by each nation along with similarities. Thus, this research seeks to find the distinctive characteristics of the Korean porcelain by conducting comparative analysis of the similarities and distinctive characteristics. These distinctive characteristics are manifested effectively in the colors of the porcelains following the materials that can be obtained in Korea, China and Japan and production method. Likewise, this research seeks to identify the characteristics of the Korean porcelains- colors based on the comparative analysis of the porcelain colors. The reasons that porcelains were selected were because they are the most well preserved cultural remains in Korea and since they have both similarities and distinctive characteristics due to the cultural interchanges among Korea, China and Japan, which facilitates comparative study. The research targets include Korea, China and Japan-s porcelains. By comparing the colors of the porcelains from Korea, China and Japan that have their distinctive characteristics, this research seeks to identify Korea-specific porcelain colors. These colors derive from the materials that can be obtained only in Korea, and they are affected by the ideologies that governed at the time. This research is meaningful in the sense that this identifies the colors that embraces the Korean culture and provides important data by leveraging the study of the characteristics of the Korea-specific porcelains.

Keywords: The colors of Korean pottery, The colors of China pottery, The colors of Japan pottery, The unique identity of Korea, Pottery History.

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Authors: Roza Dastres, Mohsen Soori

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Digital Signal Processing (DSP) is the use of digital processing systems by computers in order to perform a variety of signal processing operations. It is the mathematical manipulation of a digital signal's numerical values in order to increase quality as well as effects of signals. DSP can include linear or nonlinear operators in order to process and analyze the input signals. The nonlinear DSP processing is closely related to nonlinear system detection and can be implemented in time, frequency and space-time domains. Applications of the DSP can be presented as control systems, digital image processing, biomedical engineering, speech recognition systems, industrial engineering, health care systems, radar signal processing and telecommunication systems. In this study, advanced methods and different applications of DSP are reviewed in order to move forward the interesting research filed.

Keywords: Digital signal processing, advanced telecommunication, nonlinear signal processing, speech recognition systems.

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Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: Convolutional Neural Network, Deep Learning, Deep Learning Based FER, Facial Emotion Recognition.

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Authors: Natarajan Vijayarangan, Prasanna S. Bidare

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Cryptography, Image watermarking and E-banking are filled with apparent oxymora and paradoxes. Random sequences are used as keys to encrypt information to be used as watermark during embedding the watermark and also to extract the watermark during detection. Also, the keys are very much utilized for 24x7x365 banking operations. Therefore a deterministic random sequence is very much useful for online applications. In order to obtain the same random sequence, we need to supply the same seed to the generator. Many researchers have used Deterministic Random Number Generators (DRNGs) for cryptographic applications and Pseudo Noise Random sequences (PNs) for watermarking. Even though, there are some weaknesses in PN due to attacks, the research community used it mostly in digital watermarking. On the other hand, DRNGs have not been widely used in online watermarking due to its computational complexity and non-robustness. Therefore, we have invented a new design of generating DRNG using Pi-series to make it useful for online Cryptographic, Digital watermarking and Banking applications.

Keywords: E-tokens, LFSR, non-linear, Pi series, pseudo random number.

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Authors: Farshideh Einsele, Hassan Foroosh

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In this paper, we present a robust algorithm to recognize extracted text from grocery product images captured by mobile phone cameras. Recognition of such text is challenging since text in grocery product images varies in its size, orientation, style, illumination, and can suffer from perspective distortion. Pre-processing is performed to make the characters scale and rotation invariant. Since text degradations can not be appropriately defined using well-known geometric transformations such as translation, rotation, affine transformation and shearing, we use the whole character black pixels as our feature vector. Classification is performed with minimum distance classifier using the maximum likelihood criterion, which delivers very promising Character Recognition Rate (CRR) of 89%. We achieve considerably higher Word Recognition Rate (WRR) of 99% when using lower level linguistic knowledge about product words during the recognition process.

Keywords: Camera-based OCR, Feature extraction, Document and image processing.

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Authors: Hae-Yeoun Lee

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Quantification of cardiac function is performed by calculating blood volume and ejection fraction in routine clinical practice. However, these works have been performed by manual contouring, which requires computational costs and varies on the observer. In this paper, an automatic left ventricle segmentation algorithm on cardiac magnetic resonance images (MRI) is presented. Using knowledge on cardiac MRI, a K-mean clustering technique is applied to segment blood region on a coil-sensitivity corrected image. Then, a graph searching technique is used to correct segmentation errors from coil distortion and noises. Finally, blood volume and ejection fraction are calculated. Using cardiac MRI from 15 subjects, the presented algorithm is tested and compared with manual contouring by experts to show outstanding performance.

Keywords: Cardiac MRI, Graph searching, Left ventricle segmentation, K-means clustering.

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Currently the most prevalent deep learning methods require a large amount of data for training, whereas few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: Few-shot learning, triplet network, adaptive margin, deep learning.

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

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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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Authors: Mohammad S. Laghari, Gulzar A. Khuwaja

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Many problems in computer vision and image processing present potential for parallel implementations through one of the three major paradigms of geometric parallelism, algorithmic parallelism and processor farming. Static process scheduling techniques are used successfully to exploit geometric and algorithmic parallelism, while dynamic process scheduling is better suited to dealing with the independent processes inherent in the process farming paradigm. This paper considers the application of parallel or multi-computers to a class of problems exhibiting spatial data characteristic of the geometric paradigm. However, by using processor farming paradigm, a dynamic scheduling technique is developed to suit the MIMD structure of the multi-computers. A hybrid scheme of scheduling is also developed and compared with the other schemes. The specific problem chosen for the investigation is the Hough transform for line detection.

Keywords: Hough transforms, parallel computer, parallel paradigms, scheduling.

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Authors: Sadi Vural, Hiromi Tomii, Hironori Yamauchi

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As the development of digital technology is increasing, Digital cinema is getting more spread. However, content copy and attack against the digital cinema becomes a serious problem. To solve the above security problem, we propose “Additional Watermarking" for digital cinema delivery system. With this proposed “Additional watermarking" method, we protect content copyrights at encoder and user side information at decoder. It realizes the traceability of the watermark embedded at encoder. The watermark is embedded into the random-selected frames using Hash function. Using it, the embedding position is distributed by Hash Function so that third parties do not break off the watermarking algorithm. Finally, our experimental results show that proposed method is much better than the convenient watermarking techniques in terms of robustness, image quality and its simple but unbreakable algorithm.

Keywords: Decoder, Digital content, JPEG2000 Frame, System-On-Chip and additional watermark.

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Authors: Sepehr Aslani, Homayoun Mahdavi-Nasab

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Automated motion detection and tracking is a challenging task in traffic surveillance. In this paper, a system is developed to gather useful information from stationary cameras for detecting moving objects in digital videos. The moving detection and tracking system is developed based on optical flow estimation together with application and combination of various relevant computer vision and image processing techniques to enhance the process. To remove noises, median filter is used and the unwanted objects are removed by applying thresholding algorithms in morphological operations. Also the object type restrictions are set using blob analysis. The results show that the proposed system successfully detects and tracks moving objects in urban videos.

Keywords: Optical flow estimation, moving object detection, tracking, morphological operation, blob analysis.

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Authors: Ahmed M. S. Hussein, Sahar Y. Al-Okbi

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In the present research, whole meal barley flour (WBF) was supplemented with gelatinized corn flour (GCF) in 0 and 30%. Whole meal wheat flour (WWF) was mixed with defatted rice bran (DRB) to produce 0, 20, 25, and 30% replacement levels. Rheological properties of dough were studied. Thermal properties and starch crystallinity of flours were evaluated. Flat bread, balady bread and pie were prepared from the different flour blends. The different bakeries were sensory evaluated. Color of raw materials and crust of bakery products were determined. Nutrients contents of raw flours and food products were assessed. Results showed that addition of GCF to WBF increased the viscosity and falling number of the produced dough. Water absorption, dough development time and dough stability increased with increasing the level of DRB in dough while, weakening and mixing tolerance index decreased. Extensibility and energy decreased, while, resistance to extension increased as DRB level increased. Gelatinized temperature of WWF, WBF, GCF, and DRB were 13.26, 35.09, 28.33, and 39.63, respectively. Starch crystallinity was affected when DRB was added to WWF. The highest protein content was present in balady bread made from 70% WWF and 30% DRB. The highest calcium, phosphorus, and potassium levels were present in products made from 100% WBF. Sensory attributes of the products were slightly affected by adding DRB and GCF. Conclusion: Addition of DRB or GCF to WWF or WBF, respectively affect the physical, chemical, rheological and sensory properties of balady bread, flat bread, and pie while improved their nutritive values.

Keywords: Bakeries, rheological properties, chemical and sensory attributes, flour thermal properties and starch crystallinity.

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Authors: Sadi Vural, Hiromi Tomii, Hironori Yamauchi

Abstract:

As far as the latest technological improvements are concerned, digital systems more become popular than the past. Despite this growing demand to the digital systems, content copy and attack against the digital cinema contents becomes a serious problem. To solve the above security problem, we propose “traceable watermarking using Hash functions for digital cinema system. Digital Cinema is a great application for traceable watermarking since it uses watermarking technology during content play as well as content transmission. The watermark is embedded into the randomly selected movie frames using CRC-32 techniques. CRC-32 is a Hash function. Using it, the embedding position is distributed by Hash Function so that any party cannot break off the watermarking or will not be able to change. Finally, our experimental results show that proposed DWT watermarking method using CRC-32 is much better than the convenient watermarking techniques in terms of robustness, image quality and its simple but unbreakable algorithm.

Keywords: Decoder, Digital content, JPEG2000 Frame, System-On-Chip, traceable watermark, Hash Function, CRC-32.

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Authors: Sergio Pissanetzky

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The ability of the brain to organize information and generate the functional structures we use to act, think and communicate, is a common and easily observable natural phenomenon. In object-oriented analysis, these structures are represented by objects. Objects have been extensively studied and documented, but the process that creates them is not understood. In this work, a new class of discrete, deterministic, dissipative, host-guest dynamical systems is introduced. The new systems have extraordinary self-organizing properties. They can host information representing other physical systems and generate the same functional structures as the brain does. A simple mathematical model is proposed. The new systems are easy to simulate by computer, and measurements needed to confirm the assumptions are abundant and readily available. Experimental results presented here confirm the findings. Applications are many, but among the most immediate are object-oriented engineering, image and voice recognition, search engines, and Neuroscience.

Keywords: AI, artificial intelligence, complex system, object oriented, OO, refactoring.

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Authors: D. Dhouib, A. Naït-Ali, C. Olivier, M. S. Naceur

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In this paper, we evaluate the performance of some wavelet based coding algorithms such as 3D QT-L, 3D SPIHT and JPEG2K. In the first step we achieve an objective comparison between three coders, namely 3D SPIHT, 3D QT-L and JPEG2K. For this purpose, eight MRI head scan test sets of 256 x 256x124 voxels have been used. Results show superior performance of 3D SPIHT algorithm, whereas 3D QT-L outperforms JPEG2K. The second step consists of evaluating the robustness of 3D SPIHT and JPEG2K coding algorithm over wireless transmission. Compressed dataset images are then transmitted over AWGN wireless channel or over Rayleigh wireless channel. Results show the superiority of JPEG2K over these two models. In fact, it has been deduced that JPEG2K is more robust regarding coding errors. Thus we may conclude the necessity of using corrector codes in order to protect the transmitted medical information.

Keywords: Image coding, medical imaging, wavelet basedcoder, wireless transmission.

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: Outlier detection, generative adversary networks, semi-supervised learning.

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Authors: V. Arbabi , I. Ebrahimzadeh, H. Ghanbari, M.M. Kaykha

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Horizontal continuous casting is widely used to produce semi-finished non-Ferrous products. Homogeneity in the metallurgical characteristics and mechanical properties for this product is vital for industrial application. In the present work, the microstructure and mechanical properties of a horizontal continuous cast two-phase brass billet have been studied. Impact strength and hardness variations were examined and the phase composition and porosity studied with image analysis software. Distinct differences in mechanical properties were observed between the upper, middle and lower parts of the billet, which are explained in terms of the morphology and size of the phase in the microstructure. Hardness variation in the length of billet is higher in upper area but impact strength is higher in lower areas.

Keywords: Horizontal Continuous Casting, Two-phase brasses, CuZn40Al1 alloy, Microstructure, Impact Strength.

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Authors: Abu Bakar Sambah, Fusanori Miura

Abstract:

Remote sensing image processing, spatial data analysis through GIS approach, and analytical hierarchy process were introduced in this study for assessing the vulnerability area and inundation area due to tsunami hazard in the area of Rikuzentakata, Iwate Prefecture, Japan. Appropriate input parameters were derived from GSI DEM data, ALOS AVNIR-2, and field data. We used the parameters of elevation, slope, shoreline distance, and vegetation density. Five classes of vulnerability were defined and weighted via pairwise comparison matrix. The assessment results described that 14.35km² of the study area was under tsunami vulnerability zone. Inundation areas are those of high and slightly high vulnerability. The farthest area reached by a tsunami was about 7.50km from the shoreline and shows that rivers act as flooding strips that transport tsunami waves into the hinterland. This study can be used for determining a priority for land-use planning in the scope of tsunami hazard risk management.

Keywords: AHP, GIS, remote sensing, tsunami vulnerability.

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