Search results for: image pre-processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1615

Search results for: image pre-processing

535 Bleeding Detection Algorithm for Capsule Endoscopy

Authors: Yong-Gyu Lee, Gilwon Yoon

Abstract:

Automatic detection of bleeding is of practical importance since capsule endoscopy produces an extremely large number of images. Algorithm development of bleeding detection in the digestive tract is difficult due to different contrasts among the images, food dregs, secretion and others. In this study, were assigned weighting factors derived from the independent features of the contrast and brightness between bleeding and normality. Spectral analysis based on weighting factors was fast and accurate. Results were a sensitivity of 87% and a specificity of 90% when the accuracy was determined for each pixel out of 42 endoscope images.

Keywords: bleeding, capsule endoscopy, image analysis, weighted spectrum

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534 Streamwise Vorticity in the Wake of a Sliding Bubble

Authors: R. O’Reilly Meehan, D. B. Murray

Abstract:

In many practical situations, bubbles are dispersed in a liquid phase. Understanding these complex bubbly flows is therefore a key issue for applications such as shell and tube heat exchangers, mineral flotation and oxidation in water treatment. Although a large body of work exists for bubbles rising in an unbounded medium, that of bubbles rising in constricted geometries has received less attention. The particular case of a bubble sliding underneath an inclined surface is common to two-phase flow systems. The current study intends to expand this knowledge by performing experiments to quantify the streamwise flow structures associated with a single sliding air bubble under an inclined surface in quiescent water. This is achieved by means of two-dimensional, two-component particle image velocimetry (PIV), performed with a continuous wave laser and high-speed camera. PIV vorticity fields obtained in a plane perpendicular to the sliding surface show that there is significant bulk fluid motion away from the surface. The associated momentum of the bubble means that this wake motion persists for a significant time before viscous dissipation. The magnitude and direction of the flow structures in the streamwise measurement plane are found to depend on the point on its path through which the bubble enters the plane. This entry point, represented by a phase angle, affects the nature and strength of the vortical structures. This study reconstructs the vorticity field in the wake of the bubble, converting the field at different instances in time to slices of a large-scale wake structure. This is, in essence, Taylor’s ”frozen turbulence” hypothesis. Applying this to the vorticity fields provides a pseudo three-dimensional representation from 2-D data, allowing for a more intuitive understanding of the bubble wake. This study provides insights into the complex dynamics of a situation common to many engineering applications, particularly shell and tube heat exchangers in the nucleate boiling regime.

Keywords: Bubbly flow, particle image velocimetry, two-phase flow, wake structures.

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533 A Support System to Consult Remote another Doctor on Assessment and/or Medical Treatment Plan when a Doctor has a Patient not in His/Her Major

Authors: T. Gotoh, T. Takayama, M. Ishiki, T. Ikeda

Abstract:

Recently, majors of doctors are divided into terribly lots of detailed areas. However, it is actually not a rare case that a doctor has a patient who is not in his/her major. He/She must judge an assessment and make a medical treatment plan for this patient. According to our investigation, conventional approaches such as image diagnosis cooperation are insufficient. This paper proposes an 'Assessment / Medical Treatment Plan Consulting System'. We have implemented a pilot system based on our proposition. Its effectiveness is clarified by an evaluation.

Keywords: Application, computational intelligence and telecommunications, medicine, intelligent systems.

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532 Classification of Radio Communication Signals using Fuzzy Logic

Authors: Zuzana Dideková, Beata Mikovičová

Abstract:

Characterization of radio communication signals aims at automatic recognition of different characteristics of radio signals in order to detect their modulation type, the central frequency, and the level. Our purpose is to apply techniques used in image processing in order to extract pertinent characteristics. To the single analysis, we add several rules for checking the consistency of hypotheses using fuzzy logic. This allows taking into account ambiguity and uncertainty that may remain after the extraction of individual characteristics. The aim is to improve the process of radio communications characterization.

Keywords: fuzzy classification, fuzzy inference system, radio communication signals, telecommunications

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531 A Novel Approach to Persian Online Hand Writing Recognition

Authors: Ramin Halavati, Mansour Jamzad, Mahdieh Soleymani

Abstract:

Persian (Farsi) script is totally cursive and each character is written in several different forms depending on its former and later characters in the word. These complexities make automatic handwriting recognition of Persian a very hard problem and there are few contributions trying to work it out. This paper presents a novel practical approach to online recognition of Persian handwriting which is based on representation of inputs and patterns with very simple visual features and comparison of these simple terms. This recognition approach is tested over a set of Persian words and the results have been quite acceptable when the possible words where unknown and they were almost all correct in cases that the words where chosen from a prespecified list.

Keywords: Image Processing, Pattern Recognition.

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530 Face Recognition Using Eigen face Coefficients and Principal Component Analysis

Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Samriti Jindal, Inderpreet Kaur, Shilpi Kumari

Abstract:

Face Recognition is a field of multidimensional applications. A lot of work has been done, extensively on the most of details related to face recognition. This idea of face recognition using PCA is one of them. In this paper the PCA features for Feature extraction are used and matching is done for the face under consideration with the test image using Eigen face coefficients. The crux of the work lies in optimizing Euclidean distance and paving the way to test the same algorithm using Matlab which is an efficient tool having powerful user interface along with simplicity in representing complex images.

Keywords: Eigen Face, Multidimensional, Matching, PCA.

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529 Journals Subheadlines Text Extraction Using Wavelet Thresholding and New Projection Profile

Authors: Davod Zaravi, Habib Rostami, Alireza Malahzaheh, S. S. Mortazavi

Abstract:

In this paper a new robust and efficient algorithm to automatic text extraction from colored book and journal cover sheets is proposed. First, we perform wavelet transform. Next for edge detecting from detail wavelet coefficient, we use dynamic threshold. By blurring approximate coefficients with alternative heuristic thresholding, achieve effective edge,. Afterward, with ROI technique get binary image. Finally text boxes would be extracted with new projection profile.

Keywords: Text extraction, colored cover sheet, wavelet threshold, region of interest.

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528 Off-Line Signature Recognition Based On Angle Features and GRNN Neural Networks

Authors: Laila Y. Fannas, Ahmed Y. Ben Sasi

Abstract:

This research presents a handwritten signature recognition based on angle feature vector using Artificial Neural Network (ANN). Each signature image will be represented by an Angle vector. The feature vector will constitute the input to the ANN. The collection of signature images will be divided into two sets. One set will be used for training the ANN in a supervised fashion. The other set which is never seen by the ANN will be used for testing. After training, the ANN will be tested for recognition of the signature. When the signature is classified correctly, it is considered correct recognition otherwise it is a failure.

Keywords: Signature Recognition, Artificial Neural Network, Angle Features.

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527 Fast Extraction of Edge Histogram in DCT Domain based on MPEG7

Authors: Minyoung Eom, Yoonsik Choe

Abstract:

In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor is time-consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

Keywords: DCT, Descriptor, EHD, MPEG7.

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526 A System Functions Set-Up through Near Field Communication of a Smartphone

Authors: Jaemyoung Lee

Abstract:

We present a method to set up system functions through a near filed communication (NFC) of a smartphone. The short communication distance of the NFC which is usually less than 4 cm could prevent any interferences from other devices and establish a secure communication channel between a system and the smartphone. The proposed set-up method for system function values is demonstrated for a blacbox system in a car. In demonstration, system functions of a blackbox which is manipulated through NFC of a smartphone are controls of image quality, sound level, shock sensing level to store images, etc. The proposed set-up method for system function values can be used for any devices with NFC.

Keywords: System set-up, near field communication, smartphone, Android.

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525 Parallelization and Optimization of SIFT Feature Extraction on Cluster System

Authors: Mingling Zheng, Zhenlong Song, Ke Xu, Hengzhu Liu

Abstract:

Scale Invariant Feature Transform (SIFT) has been widely applied, but extracting SIFT feature is complicated and time-consuming. In this paper, to meet the demand of the real-time applications, SIFT is parallelized and optimized on cluster system, which is named pSIFT. Redundancy storage and communication are used for boundary data to improve the performance, and before representation of feature descriptor, data reallocation is adopted to keep load balance in pSIFT. Experimental results show that pSIFT achieves good speedup and scalability.

Keywords: cluster, image matching, parallelization and optimization, SIFT.

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524 Evolved Strokes in Non Photo–Realistic Rendering

Authors: Ashkan Izadi, Vic Ciesielski

Abstract:

We describe a work with an evolutionary computing algorithm for non photo–realistic rendering of a target image. The renderings are produced by genetic programming. We have used two different types of strokes: “empty triangle" and “filled triangle" in color level. We compare both empty and filled triangular strokes to find which one generates more aesthetic pleasing images. We found the filled triangular strokes have better fitness and generate more aesthetic images than empty triangular strokes.

Keywords: Artificial intelligence, Evolutionary programming, Geneticprogramming, Non photo–realistic rendering.

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523 Discontinuous Galerkin Method for Total Variation Minimization on Inpainting Problem

Authors: Xijian Wang

Abstract:

This paper is concerned with the numerical minimization of energy functionals in BV ( ) (the space of bounded variation functions) involving total variation for gray-scale 1-dimensional inpainting problem. Applications are shown by finite element method and discontinuous Galerkin method for total variation minimization. We include the numerical examples which show the different recovery image by these two methods.

Keywords: finite element method, discontinuous Galerkin method, total variation minimization, inpainting

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522 Tomographic Images Reconstruction Simulation for Defects Detection in Specimen

Authors: Kedit J.

Abstract:

This paper is the tomographic images reconstruction simulation for defects detection in specimen. The specimen is the thin cylindrical steel contained with low density materials. The defects in material are simulated in three shapes.The specimen image function will be transformed to projection data. Radon transform and its inverse provide the mathematical for reconstructing tomographic images from projection data. The result of the simulation show that the reconstruction images is complete for defect detection.

Keywords: Tomography, Tomography Reconstruction, Radon Transform

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521 Enhancement of a 3D Sound Using Psychoacoustics

Authors: Kyosik Koo, Hyungtai Cha

Abstract:

Generally, in order to create 3D sound using binaural systems, we use head related transfer functions (HRTF) including the information of sounds which is arrived to our ears. But it can decline some three-dimensional effects in the area of a cone of confusion between front and back directions, because of the characteristics of HRTF. In this paper, we propose a new method to use psychoacoustics theory that reduces the confusion of sound image localization. In the method, HRTF spectrum characteristic is enhanced by using the energy ratio of the bark band. Informal listening tests show that the proposed method improves the front-back sound localization characteristics much better than the conventional methods

Keywords: HRTF, 3D sound, Psychoacoustics, Localization

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520 In-Flight Radiometric Performances Analysis of an Airborne Optical Payload

Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yaokai Liu, Xinhong Wang, Yongsheng Zhou

Abstract:

Performances analysis of remote sensing sensor is required to pursue a range of scientific research and application objectives. Laboratory analysis of any remote sensing instrument is essential, but not sufficient to establish a valid inflight one. In this study, with the aid of the in situ measurements and corresponding image of three-gray scale permanent artificial target, the in-flight radiometric performances analyses (in-flight radiometric calibration, dynamic range and response linearity, signal-noise-ratio (SNR), radiometric resolution) of self-developed short-wave infrared (SWIR) camera are performed. To acquire the inflight calibration coefficients of the SWIR camera, the at-sensor radiances (Li) for the artificial targets are firstly simulated with in situ measurements (atmosphere parameter and spectral reflectance of the target) and viewing geometries using MODTRAN model. With these radiances and the corresponding digital numbers (DN) in the image, a straight line with a formulation of L = G × DN + B is fitted by a minimization regression method, and the fitted coefficients, G and B, are inflight calibration coefficients. And then the high point (LH) and the low point (LL) of dynamic range can be described as LH= (G × DNH + B) and LL= B, respectively, where DNH is equal to 2n − 1 (n is the quantization number of the payload). Meanwhile, the sensor’s response linearity (δ) is described as the correlation coefficient of the regressed line. The results show that the calibration coefficients (G and B) are 0.0083 W·sr−1m−2µm−1 and −3.5 W·sr−1m−2µm−1; the low point of dynamic range is −3.5 W·sr−1m−2µm−1 and the high point is 30.5 W·sr−1m−2µm−1; the response linearity is approximately 99%. Furthermore, a SNR normalization method is used to assess the sensor’s SNR, and the normalized SNR is about 59.6 when the mean value of radiance is equal to 11.0 W·sr−1m−2µm−1; subsequently, the radiometric resolution is calculated about 0.1845 W•sr-1m-2μm-1. Moreover, in order to validate the result, a comparison of the measured radiance with a radiative-transfer-code-predicted over four portable artificial targets with reflectance of 20%, 30%, 40%, 50% respectively, is performed. It is noted that relative error for the calibration is within 6.6%.

Keywords: Calibration, dynamic range, radiometric resolution, SNR.

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519 A New Approach for the Fingerprint Classification Based On Gray-Level Co- Occurrence Matrix

Authors: Mehran Yazdi, Kazem Gheysari

Abstract:

In this paper, we propose an approach for the classification of fingerprint databases. It is based on the fact that a fingerprint image is composed of regular texture regions that can be successfully represented by co-occurrence matrices. So, we first extract the features based on certain characteristics of the cooccurrence matrix and then we use these features to train a neural network for classifying fingerprints into four common classes. The obtained results compared with the existing approaches demonstrate the superior performance of our proposed approach.

Keywords: Biometrics, fingerprint classification, gray level cooccurrence matrix, regular texture representation.

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518 Multiplicative Functional on Upper Triangular Fuzzy Matrices

Authors: Liu Ping

Abstract:

In this paper, for an arbitrary multiplicative functional f from the set of all upper triangular fuzzy matrices to the fuzzy algebra, we prove that there exist a multiplicative functional F and a functional G from the fuzzy algebra to the fuzzy algebra such that the image of an upper triangular fuzzy matrix under f can be represented as the product of all the images of its main diagonal elements under F and other elements under G.

Keywords: Multiplicative functional, triangular fuzzy matrix, fuzzy addition operation, fuzzy multiplication operation.

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517 Face Recognition using Radial Basis Function Network based on LDA

Authors: Byung-Joo Oh

Abstract:

This paper describes a method to improve the robustness of a face recognition system based on the combination of two compensating classifiers. The face images are preprocessed by the appearance-based statistical approaches such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). LDA features of the face image are taken as the input of the Radial Basis Function Network (RBFN). The proposed approach has been tested on the ORL database. The experimental results show that the LDA+RBFN algorithm has achieved a recognition rate of 93.5%

Keywords: Face recognition, linear discriminant analysis, radial basis function network.

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516 Detecting Tomato Flowers in Greenhouses Using Computer Vision

Authors: Dor Oppenheim, Yael Edan, Guy Shani

Abstract:

This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: Agricultural engineering, computer vision, image processing, flower detection.

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515 Statistical Description in the Turbulent Near Wake of a Rotating Circular Cylinder

Authors: Sharul S. Dol, U. Azimov, Robert J. Martinuzzi

Abstract:

Turbulence studies were made in the wake of a rotating circular cylinder in a uniform free stream. The interest was to examine the turbulence properties at the suppression of periodicity in vortex formation process. An experimental study of the turbulent near wake of a rotating circular cylinder was made at a Reynolds number of 9000 for velocity ratios, λ between 0 and 2.7. Hot-wire anemometry and particle image velocimetry results indicate that the rotation of the cylinder causes significant changes in the vortical activities. The turbulence quantities are getting smaller as λ increases due to suppression of coherent vortex structures.

Keywords: Rotating circular cylinder, Reynolds stress, vortex.

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514 Optical Verification of an Ophthalmological Examination Apparatus Employing the Electroretinogram Function on Fundus-Related Perimetry

Authors: Naoto Suzuki

Abstract:

Japanese are affected by the most common causes of eyesight loss such as glaucoma, diabetic retinopathy, pigmentary retinal degeneration, and age-related macular degeneration. We developed an ophthalmological examination apparatus with a fundus camera, precisely fundus-related perimetry (microperimetry), and electroretinogram (ERG) functions to diagnose a variety of diseases that cause eyesight loss. The experimental apparatus was constructed with the same optical system as a fundus camera. The microperimetry optical system was calculated and added to the experimental apparatus using the German company Optenso's optical engineering software (OpTaliX-LT 10.8). We also added an Edmund infrared camera (EO-0413), a lens with a 25 mm focal length, a 45° cold mirror, a 12 V/50 W halogen lamp, and an 8-inch monitor. We made the artificial eye of a plane-convex lens, a black spacer, and a hemispherical cup. The hemispherical cup had a small section of the paper at the bottom. The artificial eye was photographed five times using the experimental apparatus. The software was created to display the examination target on the monitor and save examination data using C++Builder 10.2. The retinal fundus was displayed on the monitor at a length and width of 1 mm and a resolution of 70.4 ± 4.1 and 74.7 ± 6.8 pixels, respectively. The microperimetry and ERG functions were successfully added to the experimental ophthalmological apparatus. A moving machine was developed to measure the artificial eye's movement. The artificial eye's rear part was painted black and white in the central area. It was rotated 10 degrees from one side to the other. The movement was captured five times as motion videos. Three static images were extracted from one of the motion videos captured. The images display the artificial eye facing the center, right, and left directions. The three images were processed using Scilab 6.1.0 and Image Processing and Computer Vision Toolbox 4.1.2, including trimming, binarization, making a window, deleting peripheral area, and morphological operations. To calculate the artificial eye's fundus center, we added a gravity method to the program to calculate the gravity position of connected components. From the three images, the image processing could calculate the center position.

Keywords: Ophthalmological examination apparatus, microperimetry, electroretinogram, eye movement.

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513 Fast Codevector Search Algorithm for 3-D Vector Quantized Codebook

Authors: H. B. Kekre, Tanuja K. Sarode

Abstract:

This paper presents a very simple and efficient algorithm for codebook search, which reduces a great deal of computation as compared to the full codebook search. The algorithm is based on sorting and centroid technique for search. The results table shows the effectiveness of the proposed algorithm in terms of computational complexity. In this paper we also introduce a new performance parameter named as Average fractional change in pixel value as we feel that it gives better understanding of the closeness of the image since it is related to the perception. This new performance parameter takes into consideration the average fractional change in each pixel value.

Keywords: Vector Quantization, Data Compression, Encoding, Searching.

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512 Lung Nodule Detection in CT Scans

Authors: M. Antonelli, G. Frosini, B. Lazzerini, F. Marcelloni

Abstract:

In this paper we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) images. After extracting the pulmonary parenchyma using a combination of image processing techniques, a region growing method is applied to detect nodules based on 3D geometric features. We applied the CAD system to CT scans collected in a screening program for lung cancer detection. Each scan consists of a sequence of about 300 slices stored in DICOM (Digital Imaging and Communications in Medicine) format. All malignant nodules were detected and a low false-positive detection rate was achieved.

Keywords: computer assisted diagnosis, medical imagesegmentation, shape recognition.

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511 Object Localization in Medical Images Using Genetic Algorithms

Authors: George Karkavitsas, Maria Rangoussi

Abstract:

We present a genetic algorithm application to the problem of object registration (i.e., object detection, localization and recognition) in a class of medical images containing various types of blood cells. The genetic algorithm approach taken here is seen to be most appropriate for this type of image, due to the characteristics of the objects. Successful cell registration results on real life microscope images of blood cells show the potential of the proposed approach.

Keywords: Genetic algorithms, object registration, pattern recognition, blood cell microscope images.

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510 Efficient Mean Shift Clustering Using Exponential Integral Kernels

Authors: S. Sutor, R. Röhr, G. Pujolle, R. Reda

Abstract:

This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on backgrounddifferenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of nonuniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.

Keywords: Clustering, Integral Images, Kernels, Person Detection, Person Tracking, Intelligent Video Surveillance.

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509 Implementing Adaptive Steganography by Exploring the Ycbcr Color Model Characteristics

Authors: Surbhi Gupta, Alka Handa, Parvinder S.Sandhu

Abstract:

Stegnography is a new way of secret communication the most widely used mechanism on account of its simplicity is the use of the least significant bit. We have used the least significant bit (2 LSB and 4 LSB) substitution method. Depending upon the characteristics of the individual portions of cover image we decide whether to use 2 LSB or 4 LSB thus it is an adaptive stegnography technique. We used one of the three channels to behave as indicator to indicate the presence of hidden data in other two channels. The module showed impressive results in terms of capacity to hide the data. In proposed method, instead of using RGB color space directly, YCbCr color space is used to make use of human visual system characteristic.

Keywords: Stegoimage, steganography, Pixel indicator, segmentation, YCbCr..

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508 2D Bar Codes Reading: Solutions for Camera Phones

Authors: Hao Wang, Yanming Zou

Abstract:

Two-dimensional (2D) bar codes were designed to carry significantly more data with higher information density and robustness than its 1D counterpart. Thanks to the popular combination of cameras and mobile phones, it will naturally bring great commercial value to use the camera phone for 2D bar code reading. This paper addresses the problem of specific 2D bar code design for mobile phones and introduces a low-level encoding method of matrix codes. At the same time, we propose an efficient scheme for 2D bar codes decoding, of which the effort is put on solutions of the difficulties introduced by low image quality that is very common in bar code images taken by a phone camera.

Keywords: 2D bar code reading, camera phone, low-level encoding, mixed model

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507 AGV Guidance System: An Application of Simple Active Contour for Visual Tracking

Authors: M.Asif, M.R.Arshad, P.A.Wilson

Abstract:

In this paper, a simple active contour based visual tracking algorithm is presented for outdoor AGV application which is currently under development at the USM robotic research group (URRG) lab. The presented algorithm is computationally low cost and able to track road boundaries in an image sequence and can easily be implemented on available low cost hardware. The proposed algorithm used an active shape modeling using the B-spline deformable template and recursive curve fitting method to track the current orientation of the road.

Keywords: Active contour, B-spline, recursive curve fitting.

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506 Building Relationship Network for Machine Analysis from Wear Debris Measurements

Authors: Qurban A Memon, Mohammad S. Laghari

Abstract:

Integration of system process information obtained through an image processing system with an evolving knowledge database to improve the accuracy and predictability of wear debris analysis is the main focus of the paper. The objective is to automate intelligently the analysis process of wear particle using classification via self-organizing maps. This is achieved using relationship measurements among corresponding attributes of various measurements for wear debris. Finally, visualization technique is proposed that helps the viewer in understanding and utilizing these relationships that enable accurate diagnostics.

Keywords: Relationship Network, Relationship Measurement, Self-organizing Clusters, Wear Debris Analysis, Kohonen Network

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