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Image Information Processing (ICIIP), 2013 IEEE Second International Conference on

Date 9-11 Dec. 2013

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Displaying Results 1 - 25 of 143
  • Table of contents

    Publication Year: 2013 , Page(s): 1 - 12
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  • [Title page]

    Publication Year: 2013 , Page(s): 1
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  • [Copyright notice]

    Publication Year: 2013 , Page(s): 1
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  • Message from Coo and Vice Chancellor

    Publication Year: 2013 , Page(s): 1 - 2
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  • Welcome message from general chairs

    Publication Year: 2013 , Page(s): 1 - 2
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  • General chair

    Publication Year: 2013 , Page(s): 1 - 2
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  • General co-chair

    Publication Year: 2013 , Page(s): 1 - 2
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  • Conference program

    Publication Year: 2013 , Page(s): 1 - 3
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  • Detailed technical program schedule

    Publication Year: 2013 , Page(s): 1 - 24
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  • Technical program committee

    Publication Year: 2013 , Page(s): 1 - 10
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  • Organizing committee

    Publication Year: 2013 , Page(s): 1 - 3
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  • Keynote abstracts

    Publication Year: 2013 , Page(s): 1 - 5
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    These tutorials discuss the following: Color in Computer Vision; Applying computer vision methods to ecological problems; Using Computer Vision for Species Identification; Advances in blind image restoration; Biometric Recognition: Technology and Applications. View full abstract»

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  • Session chairs

    Publication Year: 2013 , Page(s): 1 - 10
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  • Author's index

    Publication Year: 2013 , Page(s): 1 - 5
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  • Lunar impact crater modeling using trinocular stereoscopic depth inpainting

    Publication Year: 2013 , Page(s): 1 - 5
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (486 KB)  

    In this paper a novel approach of stereoscopic depth inpainting is used to model lunar craters. In the case of lunar mission, the disparity map generation using stereoscopic images is limited by shadows inside impact craters. Impact craters are most important features on lunar surface but cannot be modeled using stereo cue alone. Taking into consideration the importance of crater modeling and limitations of stereo cue, we are proposing stereoscopic depth inpainting method as an additional method to model the lunar impact crater. View full abstract»

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  • Reliability assessment and prediction of open source software systems

    Publication Year: 2013 , Page(s): 6 - 11
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (551 KB) |  | HTML iconHTML  

    Affordability, redistributable, modifiability, availability of source code, zero price and freedom of choice are the characteristics which have made Open source (OS) a preferred platform for many software industries and individuals, who believe to use the power of high quality software. The technological motivation for OSS development directly relates to the software crisis, which clearly specifies that traditional development do not perform very effectively, specifically in the areas of speed, quality and cost of development. In this paper fact regarding open source software as well as different reliability concepts are elaborated. Practical implementation of OSS reliability modeling and decision making about product release has been done. For this purpose software performance measures Failure intensity, Mean Time to Failure (MTTF) and Reliability of three different open source software's failure data sets are computed and analyzed. Comparative selection of best suited Software Reliability Growth Model (SRGM) among four SRGMs for concerned data sets have been done on the basis of two comparison parameters Bias and SSE. View full abstract»

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  • Fast epipolar resampling of trinocular linear scanners images using Chandrayaan-1 TMC dataset

    Publication Year: 2013 , Page(s): 12 - 16
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (589 KB) |  | HTML iconHTML  

    In remote sensing linear scanners are widely used for acquiring stereo images as they provide data with very high resolution. A trinocular stereo view increases the accuracy of 3D modeling as it gives an additional view to compensate occlusions. However data in triplet mode by linear scanners is challenged by data processing steps which lead to a new research area for remote sensing society. In various earth and planetary missions such as ALOS PRISM, Chang'e-1, Pléiades and Chandrayaan-1 a trinocular stereo sensor was used to capture data in triplet mode. The sensor used is a linear pushbroom scanner with 3 linear array sensors looking in three directions of Aft, Nadir and Fore, which captures trinocular stereo images in along track mode. This exploration has enabled availability of large science planetary data publically but some parameters are not available as RPC parameters. Without these parameters for generation of digital elevation model (DEM), the images are required to be resampled to the epipolar geometry and then matched using area based methods. So that corresponding conjugate points can be determined, using which, parallax and finally the elevation can be estimated. In case of linear scanners, the epipolar geometry is quite challenging and it is not as straightforward as for a perspective (pin hole) frame camera. The third view gives an additional complexity to the system. These three aforestated points increase the difficulty of DEM generation for planetary missions. In this paper based on the triplet of images from linear scanner the geometrical relations are established between the three images and a method is proposed for fast epipolar resampling of triplet of images. View full abstract»

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  • Development of machine vision solution for grading of Tasar silk yarn

    Publication Year: 2013 , Page(s): 17 - 20
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (371 KB) |  | HTML iconHTML  

    Quality of Tasar fabric demands uniform coloured silk yarn during weaving. But, the variation of yarn colour depends on various natural factors like eco-race and feeding of silk worms, weather conditions etc and other production factors. So, silk yarns need to be sorted after production. At present, yarns are sorted manually by a group of experts which is subjective in nature. Again, due to lustrous nature of silk yarn, it reflects light and therefore it is difficult to ascertain the exact colour manually. Slight variation in colour is difficult to detect manually but the market demands lots with perfectly uniformly coloured yarns within the lot though the inter-lot variation in colour is encouraged. So, there is need to develop a solution which can grade the silk yarn objectively, reliably and mimic the human perception. This paper proposes a new machine vision solution for automatic grading of silk yarn based on its colour. The system consists of an enclosed cabinet which encompasses of a low cost digital camera, uniform illumination arrangement, weighing module, mechanical arrangement for sample holding and a grading software which applies image analysis technique using CIELab colour model with rotational invariant statistical feature based hierarchical grading algorithm for colour characterization. Performance of the system has been validated with the human experts and accuracy has been calculated as 91%. View full abstract»

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  • An adaptive seed point selection technique for segmentation of polarimetric synthetic aperture radar images

    Publication Year: 2013 , Page(s): 21 - 26
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1465 KB) |  | HTML iconHTML  

    The performance of the most popular unsupervised clustering algorithm, k-means depends on the initial seed points. This paper proposes a mode based adaptive seed selection algorithm, which is used to improve the performance of Wishart segmentation for the segmentation of polarimetric synthetic aperture radar images. View full abstract»

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  • Hybrid 3D registration approach using RGB and depth images

    Publication Year: 2013 , Page(s): 27 - 32
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1825 KB) |  | HTML iconHTML  

    We propose a novel technique for registration of 3D point sets using both the RGB data as well as the depth data. The main advantage of any RGB-D sensor is the pixel wise correspondence between RGB values and depth values, which can be leveraged to register two RGB-D datasets. RGB images are used for correspondence identification and these correspondences are transferred to depth images to be used for the registration algorithm. RANSAC is used for rejection of noisy data points, which increases the registration accuracy. We also analyze and present an error threshold selection strategy for fitting 3D points. Our approach achieves faster execution, thus enabling real-time implementation of change detection and 3D mapping of the environment, etc. Multiple feature extraction methods have been tested to evaluate tradeoffs between accuracy and time. View full abstract»

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  • Indian topographic map symbols understanding system

    Publication Year: 2013 , Page(s): 33 - 38
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (870 KB) |  | HTML iconHTML  

    Recognizing symbol is the first step in using a topographic map. Despite the prerequisite for extraction of information from topographic map, automated understanding of symbols is a challenging task. The objective of this paper is to explain the development of a system for automatic understanding of symbols from the Indian topographic map. The system has been developed making use of shape analysis method in which complex valued chain coding has been used for representation of the exterior boundary of the shape of the symbol. Fourier discrete transform and Auto-correlation function have been used to define shape descriptors. Classification and recognition have been implemented through template matching method and Similarity measures. The system is trained with 150 samples of each of 20 types of symbols from National digital topographic database (NTDB) for OSM of Indian topographic maps. The developed system is tested for 200 samples of each type of symbol from NTDB. It is found that 84.68% of symbols are understood correctly by the developed system. However, there are some inherent limitations in understanding the symbols from an actual map. View full abstract»

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  • Use of computer vision to detect tangles in tangled objects

    Publication Year: 2013 , Page(s): 39 - 44
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1117 KB) |  | HTML iconHTML  

    Untangling of structures like ropes and wires by autonomous robots can be useful in areas such as personal robotics, industries and electrical wiring & repairing by robots. This problem can be tackled by using computer vision system in robot. This paper proposes a computer vision based method for analyzing visual data acquired from camera for perceiving the overlap of wires, ropes, hoses i.e. detecting tangles. Information obtained after processing image according to the proposed method comprises of position of tangles in tangled object and which wire passes over which wire. This information can then be used to guide robot to untangle wire/s. Given an image, preprocessing is done to remove noise. Then edges of wire are detected. After that, the image is divided into smaller blocks and each block is checked for wire overlap/s and finding other relevant information. TANGLED-100 dataset was introduced, which consists of images of tangled linear deformable objects. Method discussed in here was tested on the TANGLED-100 dataset. Accuracy achieved during experiments was found to be 74.9%. Robotic simulations were carried out to demonstrate the use of the proposed method in applications of robot. Proposed method is a general method that can be used by robots working in different situations. View full abstract»

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  • Robust self localization by edge feature tracking

    Publication Year: 2013 , Page(s): 45 - 50
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1160 KB) |  | HTML iconHTML  

    Feature tracking algorithms have traditionally relied on point features and the use of edges as features is under-investigated. Our paper addresses the “Line segment” as the highlighted edge feature. In order to track the visible motion between two images, we have used the intersection points between pairs of line segments, which are more stable than the center or end points or any single line-segment reference. In this paper, we address at length the problems associated with segment extraction and use a method which breaks curved edge into a reliable straight line segment by putting a limit on its curvature. A straightforward approach toward tracking is discussed by defining geometric information as well as neighboring elements for a line segment feature. Finally, we conclude with a technique to reject outlier matches of line segments by using virtual intersection points to improve tracking. View full abstract»

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  • Virtual walkthrough of data centre

    Publication Year: 2013 , Page(s): 51 - 55
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1049 KB) |  | HTML iconHTML  

    Virtual reality has been common part of many domains and has drawn much attention in last few years. Virtual reality allows us to simulate the real world, or to build new worlds of our own imagining. Creating virtual reality applications has always been a critical factor for practitioners belonging to different areas such as universities, industries, and R&D sectors. This paper gives an idea for developing a virtual reality application 3D Visualization and walkthrough of Data Centre. The paper first examines underlying components and key concepts of the technology used to develop the application. The paper then elaborates the development workflow and simulation pipeline of the application. EON Studio is used to develop this application which is a complete GUI based authoring tool for developing interactive 3D applications. The application presently facilitates walkthrough of Data Centre in 3D space to monitor a specific component more closely with the help of stereo projection system, stereo eye wear, and stereo emitter. The application also provides feedback about current space utilization of the Data Centre that will help Data Centre Administrator to make key consolidation and expansion decisions. Finally the paper discusses some future enhancements to convert the existing application into pure virtual environment, in which individuals can immerse themselves fully in the virtual environment and can interact with 3D objects. View full abstract»

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  • A variational approach for optical flow estimation in infra-red or thermal images

    Publication Year: 2013 , Page(s): 56 - 61
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (694 KB) |  | HTML iconHTML  

    The most important application of the thermo vision system is the detection and tracking of moving objects in infrared images. In this paper, we have designed an approach for estimating the optical flow in thermal image sequences. This optical flow estimation approach is based on local as well as a global method which takes the advantages of both the brightness constancy assumption and spatiotemporal smoothness constraints. A new nonlinear cost function is designed with these constraints. This nonlinear cost function is minimized by the modified steepest descent method. The estimated optical flow fields demonstrate a high level of random motions caused by thermal noise. The experimental results show the robustness of the proposed method. View full abstract»

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