Search results for: fringing field effect and image charges.
7711 New Robust Approach of Direct Field Oriented Control of Induction Motor
Authors: T. Benmiloud, A. Omari
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This paper presents a new technique of compensation of the effect of variation parameters in the direct field oriented control of induction motor. The proposed method uses an adaptive tuning of the value of synchronous speed to obtain the robustness for the field oriented control. We show that this adaptive tuning allows having robustness for direct field oriented control to changes in rotor resistance, load torque and rotational speed. The effectiveness of the proposed control scheme is verified by numerical simulations. The numerical validation results of the proposed scheme have presented good performances compared to the usual direct-field oriented control.Keywords: Induction motor, direct field-oriented control, compensation of variation parameters, fuzzy logic controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18547710 Improving the Performance of Deep Learning in Facial Emotion Recognition with Image Sharpening
Authors: Ksheeraj Sai Vepuri, Nada Attar
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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.Keywords: Facial expression recognition, image pre-processing, deep learning, CNN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5287709 Colour Image Compression Method Based On Fractal Block Coding Technique
Authors: Dibyendu Ghoshal, Shimal Das
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Image compression based on fractal coding is a lossy compression method and normally used for gray level images range and domain blocks in rectangular shape. Fractal based digital image compression technique provide a large compression ratio and in this paper, it is proposed using YUV colour space and the fractal theory which is based on iterated transformation. Fractal geometry is mainly applied in the current study towards colour image compression coding. These colour images possesses correlations among the colour components and hence high compression ratio can be achieved by exploiting all these redundancies. The proposed method utilises the self-similarity in the colour image as well as the cross-correlations between them. Experimental results show that the greater compression ratio can be achieved with large domain blocks but more trade off in image quality is good to acceptable at less than 1 bit per pixel.
Keywords: Fractal coding, Iterated Function System (IFS), Image compression, YUV colour space.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19657708 Electric Field Impact on the Biomass Gasification and Combustion Dynamics
Authors: M. Zake, I. Barmina, A. Kolmickovs, R. Valdmanis
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Experimental investigations of the DC electric field effect on thermal decomposition of biomass, formation of the axial flow of volatiles (CO, H2, CxHy), mixing of volatiles with swirling airflow at low swirl intensity (S ≈ 0.2-0.35), their ignition and on formation of combustion dynamics are carried out with the aim to understand the mechanism of electric field influence on biomass gasification, combustion of volatiles and heat energy production. The DC electric field effect on combustion dynamics was studied by varying the positive bias voltage of the central electrode from 0.6 kV to 3 kV, whereas the ion current was limited to 2 mA. The results of experimental investigations confirm the field-enhanced biomass gasification with enhanced release of volatiles and the development of endothermic processes at the primary stage of thermochemical conversion of biomass determining the field-enhanced heat energy consumption with the correlating decrease of the flame temperature and heat energy production at this stage of flame formation. Further, the field-enhanced radial expansion of the flame reaction zone correlates with a more complete combustion of volatiles increasing the combustion efficiency by 3% and decreasing the mass fraction of CO, H2 and CxHy in the products, whereas by 10% increases the average volume fraction of CO2 and the heat energy production downstream the combustor increases by 5-10%
Keywords: Biomass, combustion, electrodynamic control, gasification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16027707 An Artificial Intelligent Technique for Robust Digital Watermarking in Multiwavelet Domain
Authors: P. Kumsawat, K. Pasitwilitham, K. Attakitmongcol, A. Srikaew
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In this paper, an artificial intelligent technique for robust digital image watermarking in multiwavelet domain is proposed. The embedding technique is based on the quantization index modulation technique and the watermark extraction process does not require the original image. We have developed an optimization technique using the genetic algorithms to search for optimal quantization steps to improve the quality of watermarked image and robustness of the watermark. In addition, we construct a prediction model based on image moments and back propagation neural network to correct an attacked image geometrically before the watermark extraction process begins. The experimental results show that the proposed watermarking algorithm yields watermarked image with good imperceptibility and very robust watermark against various image processing attacks.Keywords: Watermarking, Multiwavelet, Quantization index modulation, Genetic algorithms, Neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20847706 Contrast Enhancement in Digital Images Using an Adaptive Unsharp Masking Method
Authors: Z. Mortezaie, H. Hassanpour, S. Asadi Amiri
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Captured images may suffer from Gaussian blur due to poor lens focus or camera motion. Unsharp masking is a simple and effective technique to boost the image contrast and to improve digital images suffering from Gaussian blur. The technique is based on sharpening object edges by appending the scaled high-frequency components of the image to the original. The quality of the enhanced image is highly dependent on the characteristics of both the high-frequency components and the scaling/gain factor. Since the quality of an image may not be the same throughout, we propose an adaptive unsharp masking method in this paper. In this method, the gain factor is computed, considering the gradient variations, for individual pixels of the image. Subjective and objective image quality assessments are used to compare the performance of the proposed method both with the classic and the recently developed unsharp masking methods. The experimental results show that the proposed method has a better performance in comparison to the other existing methods.Keywords: Unsharp masking, blur image, sub-region gradient, image enhancement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13957705 Volterra Filter for Color Image Segmentation
Authors: M. B. Meenavathi, K. Rajesh
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Color image segmentation plays an important role in computer vision and image processing areas. In this paper, the features of Volterra filter are utilized for color image segmentation. The discrete Volterra filter exhibits both linear and nonlinear characteristics. The linear part smoothes the image features in uniform gray zones and is used for getting a gross representation of objects of interest. The nonlinear term compensates for the blurring due to the linear term and preserves the edges which are mainly used to distinguish the various objects. The truncated quadratic Volterra filters are mainly used for edge preserving along with Gaussian noise cancellation. In our approach, the segmentation is based on K-means clustering algorithm in HSI space. Both the hue and the intensity components are fully utilized. For hue clustering, the special cyclic property of the hue component is taken into consideration. The experimental results show that the proposed technique segments the color image while preserving significant features and removing noise effects.Keywords: Color image segmentation, HSI space, K–means clustering, Volterra filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18467704 Application of Fuzzy Neural Network for Image Tumor Description
Authors: Nahla Ibraheem Jabbar, Monica Mehrotra
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This paper used a fuzzy kohonen neural network for medical image segmentation. Image segmentation plays a important role in the many of medical imaging applications by automating or facilitating the diagnostic. The paper analyses the tumor by extraction of the features of (area, entropy, means and standard deviation).These measurements gives a description for a tumor.
Keywords: FCM, features extraction, medical image processing, neural network, segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21037703 A Quantum-Inspired Evolutionary Algorithm forMultiobjective Image Segmentation
Authors: Hichem Talbi, Mohamed Batouche, Amer Draa
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In this paper we present a new approach to deal with image segmentation. The fact that a single segmentation result do not generally allow a higher level process to take into account all the elements included in the image has motivated the consideration of image segmentation as a multiobjective optimization problem. The proposed algorithm adopts a split/merge strategy that uses the result of the k-means algorithm as input for a quantum evolutionary algorithm to establish a set of non-dominated solutions. The evaluation is made simultaneously according to two distinct features: intra-region homogeneity and inter-region heterogeneity. The experimentation of the new approach on natural images has proved its efficiency and usefulness.Keywords: Image segmentation, multiobjective optimization, quantum computing, evolutionary algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23467702 Face Texture Reconstruction for Illumination Variant Face Recognition
Authors: Pengfei Xiong, Lei Huang, Changping Liu
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In illumination variant face recognition, existing methods extracting face albedo as light normalized image may lead to loss of extensive facial details, with light template discarded. To improve that, a novel approach for realistic facial texture reconstruction by combining original image and albedo image is proposed. First, light subspaces of different identities are established from the given reference face images; then by projecting the original and albedo image into each light subspace respectively, texture reference images with corresponding lighting are reconstructed and two texture subspaces are formed. According to the projections in texture subspaces, facial texture with normal light can be synthesized. Due to the combination of original image, facial details can be preserved with face albedo. In addition, image partition is applied to improve the synthesization performance. Experiments on Yale B and CMUPIE databases demonstrate that this algorithm outperforms the others both in image representation and in face recognition.Keywords: texture reconstruction, illumination, face recognition, subspaces
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14727701 Segmentation of Images through Clustering to Extract Color Features: An Application forImage Retrieval
Authors: M. V. Sudhamani, C. R. Venugopal
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This paper deals with the application for contentbased image retrieval to extract color feature from natural images stored in the image database by segmenting the image through clustering. We employ a class of nonparametric techniques in which the data points are regarded as samples from an unknown probability density. Explicit computation of the density is avoided by using the mean shift procedure, a robust clustering technique, which does not require prior knowledge of the number of clusters, and does not constrain the shape of the clusters. A non-parametric technique for the recovery of significant image features is presented and segmentation module is developed using the mean shift algorithm to segment each image. In these algorithms, the only user set parameter is the resolution of the analysis and either gray level or color images are accepted as inputs. Extensive experimental results illustrate excellent performance.Keywords: Segmentation, Clustering, Image Retrieval, Features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14517700 Weed Classification using Histogram Maxima with Threshold for Selective Herbicide Applications
Authors: Irshad Ahmad, Abdul Muhamin Naeem, Muhammad Islam, Shahid Nawaz
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Information on weed distribution within the field is necessary to implement spatially variable herbicide application. Since hand labor is costly, an automated weed control system could be feasible. This paper deals with the development of an algorithm for real time specific weed recognition system based on Histogram Maxima with threshold of an image that is used for the weed classification. This algorithm is specifically developed to classify images into broad and narrow class for real-time selective herbicide application. The developed system has been tested on weeds in the lab, which have shown that the system to be very effectiveness in weed identification. Further the results show a very reliable performance on images of weeds taken under varying field conditions. The analysis of the results shows over 95 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.Keywords: Image processing, real-time recognition, weeddetection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21497699 A Novel VLSI Architecture of Hybrid Image Compression Model based on Reversible Blockade Transform
Authors: C. Hemasundara Rao, M. Madhavi Latha
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Image compression can improve the performance of the digital systems by reducing time and cost in image storage and transmission without significant reduction of the image quality. Furthermore, the discrete cosine transform has emerged as the new state-of-the art standard for image compression. In this paper, a hybrid image compression technique based on reversible blockade transform coding is proposed. The technique, implemented over regions of interest (ROIs), is based on selection of the coefficients that belong to different transforms, depending on the coefficients is proposed. This method allows: (1) codification of multiple kernals at various degrees of interest, (2) arbitrary shaped spectrum,and (3) flexible adjustment of the compression quality of the image and the background. No standard modification for JPEG2000 decoder was required. The method was applied over different types of images. Results show a better performance for the selected regions, when image coding methods were employed for the whole set of images. We believe that this method is an excellent tool for future image compression research, mainly on images where image coding can be of interest, such as the medical imaging modalities and several multimedia applications. Finally VLSI implementation of proposed method is shown. It is also shown that the kernal of Hartley and Cosine transform gives the better performance than any other model.Keywords: VLSI, Discrete Cosine Transform, JPEG, Hartleytransform, Radon Transform
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18247698 The Effect of the Crystal Field Interaction on the Critical Temperatures and the Sublattice Magnetizations of a Mixed Spin-3/2 and Spin-5/2 Ferrimagnetic System
Authors: Fathi Abubrig, Mohamed Delfag, Suad M. Abuzariba
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The influence of the crystal field interactions on the mixed spin-3/2 and spin-5/2 ferrimagnetic Ising system is considered by using the mean field theory based on Bogoliubov inequality for the Gibbs free energy. The ground-state phase diagram is constructed, the phase diagrams of the second-order critical temperatures are obtained, and the thermal variation of the sublattice magnetizations is investigated in detail. We find some interesting phenomena for the sublattice magnetizations at particular values of the crystal field interactions.
Keywords: Crystal field, Ising system, Ferrimagnetic, magnetization, phase diagrams.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21297697 Design of a Novel Inclination Sensor Utilizing Grayscale Image
Authors: Tuhin Subhra Sarkar, Subir Das
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Several research works have been done in recent times utilizing grayscale image for the measurement of many physical phenomena. In this present paper, we have designed an embedded based inclination sensor utilizing the grayscale image with a resolution of 0.3º. The sensor module consists of a circular shaped metal disc, laminated with grayscale image and an optical transreceiver. The sensor principle is based on temporal changes in light intensity by the movement of grayscale image with the inclination of the target surface and the variation of light intensity has been detected in terms of voltage by the signal processing circuit (SPC).The output of SPC is fed to a microcontroller program to display the inclination angel digitally. The experimental results are shown a satisfactory performance of the sensor in a small inclination measuring range of -40º to + 40º with a sensitivity of 62 mV/°.
Keywords: Grayscale image, Inclination Sensor, Microcontroller Program, Signal Processing Circuit.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18117696 Measurement and Analysis of Temperature Effects on Box Girders of Continuous Rigid Frame Bridges
Authors: Bugao Wang, Weifeng Wang, Xianwei Zeng
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Researches on the general rules of temperature field changing and their effects on the bridge in construction are necessary. This paper investigated the rules of temperature field changing and its effects on bridge using onsite measurement and computational analysis. Guanyinsha Bridge was used as a case study in this research. The temperature field was simulated in analyses. The effects of certain boundary conditions such as sun radiance, wind speed, and model parameters such as heat factor and specific heat on temperature field are investigated. Recommended values for these parameters are proposed. The simulated temperature field matches the measured observations with high accuracy. At the same time, the stresses and deflections of the bridge computed with the simulated temperature field matches measured values too. As a conclusion, the temperature effect analysis of reinforced concrete box girder can be conducted directly based on the reliable weather data of the concerned area.Keywords: continuous rigid frame bridge, temperature effectanalysis, temperature field, temperature field simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25657695 Performance Evaluation of Content Based Image Retrieval Using Indexed Views
Authors: Tahir Iqbal, Mumtaz Ali, Syed Wajahat Kareem, Muhammad Harris
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Digital information is expanding in exponential order in our life. Information that is residing online and offline are stored in huge repositories relating to every aspect of our lives. Getting the required information is a task of retrieval systems. Content based image retrieval (CBIR) is a retrieval system that retrieves the required information from repositories on the basis of the contents of the image. Time is a critical factor in retrieval system and using indexed views with CBIR system improves the time efficiency of retrieved results.
Keywords: Content based image retrieval (CBIR), Indexed view, Color, Image retrieval, Cross correlation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18477694 Image Distortion Correction Method of 2-MHz Side Scan Sonar for Underwater Structure Inspection
Authors: Youngseok Kim, Chul Park, Jonghwa Yi, Sangsik Choi
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The 2-MHz Side Scan SONAR (SSS) attached to the boat for inspection of underwater structures is affected by shaking. It is difficult to determine the exact scale of damage of structure. In this study, a motion sensor is attached to the inside of the 2-MHz SSS to get roll, pitch, and yaw direction data, and developed the image stabilization tool to correct the sonar image. We checked that reliable data can be obtained with an average error rate of 1.99% between the measured value and the actual distance through experiment. It is possible to get the accurate sonar data to inspect damage in underwater structure.
Keywords: Image stabilization, motion sensor, safety inspection, sonar image, underwater structure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10467693 A Robust Image Steganography Method Using PMM in Bit Plane Domain
Authors: Souvik Bhattacharyya, Aparajita Khan, Indradip Banerjee, Gautam Sanyal
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Steganography is the art and science that hides the information in an appropriate cover carrier like image, text, audio and video media. In this work the authors propose a new image based steganographic method for hiding information within the complex bit planes of the image. After slicing into bit planes the cover image is analyzed to extract the most complex planes in decreasing order based on their bit plane complexity. The complexity function next determines the complex noisy blocks of the chosen bit plane and finally pixel mapping method (PMM) has been used to embed secret bits into those regions of the bit plane. The novel approach of using pixel mapping method (PMM) in bit plane domain adaptively embeds data on most complex regions of image, provides high embedding capacity, better imperceptibility and resistance to steganalysis attack.
Keywords: PMM (Pixel Mapping Method), Bit Plane, Steganography, SSIM, KL-Divergence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28557692 Hand Vein Image Enhancement With Radon Like Features Descriptor
Authors: Randa Boukhris Trabelsi, Alima Damak Masmoudi, Dorra Sellami Masmoudi
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Nowadays, hand vein recognition has attracted more attentions in identification biometrics systems. Generally, hand vein image is acquired with low contrast and irregular illumination. Accordingly, if you have a good preprocessing of hand vein image, we can easy extracted the feature extraction even with simple binarization. In this paper, a proposed approach is processed to improve the quality of hand vein image. First, a brief survey on existing methods of enhancement is investigated. Then a Radon Like features method is applied to preprocessing hand vein image. Finally, experiments results show that the proposed method give the better effective and reliable in improving hand vein images.
Keywords: Hand Vein, Enhancement, Contrast, RLF, SDME
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22277691 CBIR Using Multi-Resolution Transform for Brain Tumour Detection and Stages Identification
Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian
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Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.
Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7567690 Adaptive Block State Update Method for Separating Background
Authors: Youngsuck Ji, Youngjoon Han, Hernsoo Hahn
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In this paper, we proposed the robust mobile object detection method for light effect in the night street image block based updating reference background model using block state analysis. Experiment image is acquired sequence color video from steady camera. When suddenly appeared artificial illumination, reference background model update this information such as street light, sign light. Generally natural illumination is change by temporal, but artificial illumination is suddenly appearance. So in this paper for exactly detect artificial illumination have 2 state process. First process is compare difference between current image and reference background by block based, it can know changed blocks. Second process is difference between current image-s edge map and reference background image-s edge map, it possible to estimate illumination at any block. This information is possible to exactly detect object, artificial illumination and it was generating reference background more clearly. Block is classified by block-state analysis. Block-state has a 4 state (i.e. transient, stationary, background, artificial illumination). Fig. 1 is show characteristic of block-state respectively [1]. Experimental results show that the presented approach works well in the presence of illumination variance.Keywords: Block-state, Edge component, Reference backgroundi, Artificial illumination.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13137689 Sequential Partitioning Brainbow Image Segmentation Using Bayesian
Authors: Yayun Hsu, Henry Horng-Shing Lu
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This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate crosstalk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds, since biological information is inherently included inside the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.
Keywords: Brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22477688 On the Use of Image Processing Techniques for the Estimation of the Porosity of Textile Fabrics
Authors: Ahmet Çay, Savvas Vassiliadis, Maria Rangoussi, Işık Tarakçıoğlu
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This paper presents a novel approach to assessing textile porosity by the application of the image analysis techniques. The images of different types of sample fabrics, taken through a microscope when the fabric is placed over a constant light source,transfer the problem into the image analysis domain. Indeed, porosity can thus be expressed in terms of a brightness percentage index calculated on the digital microscope image. Furthermore, it is meaningful to compare the brightness percentage index with the air permeability and the tightness indices of each fabric type. We have experimentally shown that there exists an approximately linear relation between brightness percentage and air permeability indices.
Keywords: Textile fabrics, porosity, air permeability, image analysis, light transmission.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32607687 Image Authenticity and Perceptual Optimization via Genetic Algorithm and a Dependence Neighborhood
Authors: Imran Usman, Asifullah Khan, Rafiullah Chamlawi, Abdul Majid
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Information hiding for authenticating and verifying the content integrity of the multimedia has been exploited extensively in the last decade. We propose the idea of using genetic algorithm and non-deterministic dependence by involving the un-watermarkable coefficients for digital image authentication. Genetic algorithm is used to intelligently select coefficients for watermarking in a DCT based image authentication scheme, which implicitly watermark all the un-watermarkable coefficients also, in order to thwart different attacks. Experimental results show that such intelligent selection results in improvement of imperceptibility of the watermarked image, and implicit watermarking of all the coefficients improves security against attacks such as cover-up, vector quantization and transplantation.
Keywords: Digital watermarking, fragile watermarking, geneticalgorithm, Image authentication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15117686 Effect of Scene Changing on Image Sequences Compression Using Zero Tree Coding
Authors: Mbainaibeye Jérôme, Noureddine Ellouze
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We study in this paper the effect of the scene changing on image sequences coding system using Embedded Zerotree Wavelet (EZW). The scene changing considered here is the full motion which may occurs. A special image sequence is generated where the scene changing occurs randomly. Two scenarios are considered: In the first scenario, the system must provide the reconstruction quality as best as possible by the management of the bit rate (BR) while the scene changing occurs. In the second scenario, the system must keep the bit rate as constant as possible by the management of the reconstruction quality. The first scenario may be motivated by the availability of a large band pass transmission channel where an increase of the bit rate may be possible to keep the reconstruction quality up to a given threshold. The second scenario may be concerned by the narrow band pass transmission channel where an increase of the bit rate is not possible. In this last case, applications for which the reconstruction quality is not a constraint may be considered. The simulations are performed with five scales wavelet decomposition using the 9/7-tap filter bank biorthogonal wavelet. The entropy coding is performed using a specific defined binary code book and EZW algorithm. Experimental results are presented and compared to LEAD H263 EVAL. It is shown that if the reconstruction quality is the constraint, the system increases the bit rate to obtain the required quality. In the case where the bit rate must be constant, the system is unable to provide the required quality if the scene change occurs; however, the system is able to improve the quality while the scene changing disappears.Keywords: Image Sequence Compression, Wavelet Transform, Scene Changing, Zero Tree, Bit Rate, Quality.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13487685 Machine Vision System for Automatic Weeding Strategy in Oil Palm Plantation using Image Filtering Technique
Authors: Kamarul Hawari Ghazali, Mohd. Marzuki Mustafa, Aini Hussain
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Machine vision is an application of computer vision to automate conventional work in industry, manufacturing or any other field. Nowadays, people in agriculture industry have embarked into research on implementation of engineering technology in their farming activities. One of the precision farming activities that involve machine vision system is automatic weeding strategy. Automatic weeding strategy in oil palm plantation could minimize the volume of herbicides that is sprayed to the fields. This paper discusses an automatic weeding strategy in oil palm plantation using machine vision system for the detection and differential spraying of weeds. The implementation of vision system involved the used of image processing technique to analyze weed images in order to recognized and distinguished its types. Image filtering technique has been used to process the images as well as a feature extraction method to classify the type of weed images. As a result, the image processing technique contributes a promising result of classification to be implemented in machine vision system for automated weeding strategy.Keywords: Machine vision, Automatic Weeding Strategy, filter, feature extraction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18547684 Globally Convergent Edge-preserving Reconstruction with Contour-line Smoothing
Authors: Marc C. Robini, Pierre-Jean Viverge, Yuemin Zhu, Jianhua Luo
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The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computationally expensive or produce disappointing results. In this paper, we propose to incorporate the smoothness of the edge field in an implicit way by means of an additional penalty term defined in the wavelet domain. We also derive an efficient half-quadratic algorithm to solve the resulting optimization problem, including the case when the data fidelity term is non-quadratic and the cost function is nonconvex. Numerical experiments show that our technique preserves edge sharpness while smoothing contour lines; it produces visually pleasing reconstructions which are quantitatively better than those obtained without wavelet-domain constraints.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13347683 Fast Depth Estimation with Filters
Authors: Yiming Nie, Tao Wu, Xiangjing An, Hangen He
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Fast depth estimation from binocular vision is often desired for autonomous vehicles, but, most algorithms could not easily be put into practice because of the much time cost. We present an image-processing technique that can fast estimate depth image from binocular vision images. By finding out the lines which present the best matched area in the disparity space image, the depth can be estimated. When detecting these lines, an edge-emphasizing filter is used. The final depth estimation will be presented after the smooth filter. Our method is a compromise between local methods and global optimization.Keywords: Depth estimation, image filters, stereo match.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12417682 Investigation of Corona wind Effect on Heat and Mass Transfer Enhancement
Authors: R.Karami, B.Kamkari, K.Kashefi
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Applying corona wind as a novel technique can lead to a great level of heat and mass transfer augmentation by using very small amount of energy. Enhancement of forced flow evaporation rate by applying electric field (corona wind) has been experimentally evaluated in this study. Corona wind produced by a fine wire electrode which is charged with positive high DC voltage impinges to water surface and leads to evaporation enhancement by disturbing the saturated air layer over water surface. The study was focused on the effect of corona wind velocity, electrode spacing and air flow velocity on the level of evaporation enhancement. Two sets of experiments, i.e. with and without electric field, have been conducted. Data obtained from the first experiment were used as reference for evaluation of evaporation enhancement at the presence of electric field. Applied voltages ranged from corona threshold voltage to spark over voltage at 1 kV increments. The results showed that corona wind has great enhancement effect on water evaporation rate, but its effectiveness gradually diminishes by increasing air flow velocity. Maximum enhancements were 7.3 and 3.6 for air velocities of 0.125 and 1.75 m/s, respectively.Keywords: Electrohydodynamics (EHD), corona wind, high electric field, Evaporation enhancement
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1887