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Journal Cover   International Journal of Research in Computer and Communication Technology
  [2 followers]  Follow
    
  This is an Open Access Journal Open Access journal
   ISSN (Print) 2320-5156 - ISSN (Online) 2278-5841
   Published by Suryansh Publications Homepage  [2 journals]
  • Implementation and Analysis of Modeling of Brain Surgery Simulation for
           Patient

    • Authors: Nukala Madhuri, T.Muni Reddy
      Abstract: A proposed real-time neurosurgery simulator handles skull drilling and surgical interaction with the brain. This involves the development and combination of areas such as collision handling, haptic rendering, physical simulation, and volumetric visualization. The simulator's input data comes from computed tomography (CT) and magnetic-resonance-imaging images of the patients. Collision detection for drilling uses only density data; collision detection for interaction with the brain is based on uniform spatial subdivision of a tetrahedral mesh. To take advantage of all the information, the simulator employs visualization methods such as volumetric issosurfaces and deformable volume rendering
      PubDate: 2015-08-01
      Issue No: Vol. 4 (2015)
       
  • Text Detection On Scene Images Using MSER

    • Authors: Venkateswarlu Kethineni, Sreerama Murthy Velaga
      Abstract: Text detection and recognition is one of the difficult tasks in the computer vision community and there is a lot of research going on in recent years. This paper focuses on the problem of text detection and recognition from scene images. We propose a novel approach to recognize the text from the scene images. First, we detect Maximally Stable Extremal Regions (MSER) from the input image. Then the image containing MSER region is fed as input to the canny edge detector, which produces edges over text region and helps us to remove the remaining part of the image by applying filtering technique. Finally text region image is given to the Optical Character Recognition (OCR). The OCR produces the actual text presented in the input image.
      PubDate: 2015-08-01
      Issue No: Vol. 4 (2015)
       
  • Implementation and Analysis of Power-constrained contrast enhancement
           algorithm using a sub-band decomposed MSRA for OLED display

    • Authors: Nukala prasanthi
      Abstract: This paper presents a power-constrained contrast enhancement algorithm for organic light-emitting diode display based on multi-scale retinex Algorithm (MSRA). In general, MSR, which is the key component of the proposed algorithm, consists of power controllable log operation and sub-band wise gain control. First, we decompose an input image to MSRAs of different sub-bands, and compute a proper gain for each MSRA. Second, we administer a coarse-to-fine ability ascendancy mechanism, which recomputed the MSRAs and gains. This footfall iterates until the ambition ability extenuative is accurately accomplished. With video sequences, the adverse levels of adjoining images are bent consistently application banausic adherence in adjustment to abstain ablaze artifacts. Finally, we present several enhancement abilities for real-time processing. Experimental after-effects appearance that the proposed algorithm provides bigger beheld superior than antecedent methods, and a constant power-saving arrangement after ablaze artifacts, even for video sequences.
      PubDate: 2015-08-01
      Issue No: Vol. 4 (2015)
       
  • Implementation and Analysis of Image Contrast Enhancement using Gaussian
           Mixture Model

    • Authors: Swetha Kanuparthy, Prasad V
      Abstract: In this paper, we propose a new global contrast enhancement algorithm using the histogram color and depth images. On the basis of the histogram-modification framework, the color and depth image histograms are first partitioned into sub- intervals using the Gaussian mixture model. The positions partitioning the color histogram are then adjusted such that spatially neighboring pixels with the similar intensity and depth values can be  grouped into the same sub-interval. By estimating the mapping curve of the contrast enhancement for each sub-interval, the global image contrast can be improved without over-enhancing the local image contrast.  Experimental results demonstrate the effectiveness of the proposed algorithm. The current major project in contrast enhancement is to partition the input histogram into multiple sub histograms before final equalization of each sub-histogram is performed. This paper presents a novel contrast enhancement method based on Gaussian mixture modeling of image histograms, which provides a sound theoretical underpinning of the partitioning process .By estimating the mapping curve of the contrast enhancement for each sub-interval, the global image contrast can be improved without over-enhancing the local image contrast.
      PubDate: 2015-08-01
      Issue No: Vol. 4 (2015)
       
  • Big Data Analytics for Net Flow Analysis in Distributed Environment using
           Hadoop

    • Authors: Amreesh Kumar Patel, D.S. Bhilare, Sushil buriya, Satyendra Singh Yadav
      Abstract: Network traffic measurement and analysis have been regularly performed on a high performance server that collects and analysis packet flow. When we monitor a large volume of network traffic data for detailed statistics, a large-scale network, it is not easy to handle Tera or Peta byte data with a single server, there is need to thousands of machines. As distributed parallel processing scheme have been recently developed due to the cluster file system, which beneficially applied to analyzing big network traffic data. Hadoop is a popular parallel processing framework that is widely used for working with large datasets. We analyze the netflow data monitoring single node to multi nodes hadoop cluster and provide an algorithm to calculate packet count and packet size of each source ip address for every fix interval of time, with low rate of false positives to detect malicious activity. Finally, we highlight performance and benefits of hadoop distributed cluster when we used large data sets as well as small data sets.
      PubDate: 2015-07-30
      Issue No: Vol. 4 (2015)
       
  • ECG Noise Reduction by Different Filters: A Comparative Analysis

    • Authors: Ankit Gupta, Sulata Bhandari
      Abstract: The electrocardiogram (ECG or EKG) is a diagnostic tool that measures and records the electrical activity of the heart in exquisite detail. The electrocardiogram is commonly used to detect abnormal heart rhythms and to investigate the cause of chest pains, thus it is very important signal in cardiology. While recording noise, sources  like the power line interference and other  noise sources distorts the original ecg signal. This paper presents  a comparative analysis  of performances of  various filters using approximations like Butterworth and Chebychev, on ECG noise filtration.
      PubDate: 2015-07-30
      Issue No: Vol. 4 (2015)
       
  • Performance Enhancement of Sliding Mode Control Using Fuzzy Logic: An
           Application And Analysis

    • Authors: Arpit Chugh, Sulata Bhandari
      Abstract: Sliding mode control (SMC) is an efficient tool in design of robust controller for nonlinear plants.  The main advantage of sliding mode control is order reduction and making the system practically independent of variation in plant parameter. With faster switching circuits sliding mode control is proving to be a great tool. The inherent problem of sliding mode control is chattering. Out of the numerous possibilities fuzzy logic controllers are the best option. Many researches have been done in this field. This paper presents the application of SMC. An inverted pendulum system and a physical world problem of underwater vehicle are presented for analysis. The problem of chattering is then addressed. Fuzzy logic is next applied to improve the performance obtained by SMC.
      PubDate: 2015-07-30
      Issue No: Vol. 4 (2015)
       
 
 
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