Unconstrained Handwritten Text Line Segmentation: An Improved Technique

Vol.1  No.4

Year : 2014

Issue : Oct-Dec

Title : Unconstrained Handwritten Text Line Segmentation: An Improved Technique

Author Name :  kiran, Mohammadi , Manjunath Aradhya

Synopsis : 

Handwritten text line segmentation is still a challenging area in document image analysis. This is due to the variation of handwritten style from individual to individual causing many problems like multi-skewed, overlapping and touching text lines. In this paper, authors have proposed an improved technique for handwritten text line segmentation to the method proposed in [1]. The proposed method consists of four major phases, which includes piece-wise painting algorithm, skew estimation, line drawing and edge detection process. The proposed method is implemented on dataset of Kannada, English and comprising of Persian, Oriya and Bangla documents. The success rate of the technique, as observed experimentally was satisfactory and it may contribute significantly for the development of applications related to handwritten OCR (Optical Character Recognition).

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An investigation of Various Image Denoising Filter for Gray Scale and color Images

Vol.1  No.4

Year : 2014

Issue : Oct-Dec

Title : An investigation of Various Image Denoising Filter for Gray Scale and color Images

Author Name : Murugan V, Avudaiappan , Balasubramanian

Synopsis : 

A variety of medical and satelite images are essential as sources of in sequence for study and understanding. When an image is transformed from one form to another such as scanning, transmitting, digitizing, storing etc., degradation occurs to the output image. For this reason, the output image wants to be better in order to be recovered . This paper presents a detailed survey on various noise detection and reduction algorithms. Different noises will affect the image in different ways. A detailed survey of the research is needed in order to design the filter which will execute the needed aspects along with handling most of the image filtering issues

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Identification Of Volcano Hotspots By Using Resilient Back Propagation (RBP) Algorithm Via Satellite Images

Vol.1  No.4

Year : 2014

Issue : Oct-Dec

Title : Identification Of Volcano Hotspots By Using Resilient Back Propagation (RBP) Algorithm Via Satellite Images

Author Name : MUNI RATHNAM S, Dr.T.Ramashri

Synopsis : 

The explosive growth of remote sensing technology, internet and multimedia systems poses great challenge in handling huge amount of data. Advancement in the field of Remote Sensing has gone to an extent of taking the geospatial accuracy to few centimeters. The use of remote sensing of natural hazards and disasters has become common. Remote sensing plays a vital role because of their pressing need in the analysis of natural hazards. Among the various hazards, the Volcanoes are terrific hazards which may harm the nature as well as the living things. Here, the identification of volcanoes and their hotspot identification are important to protect the living things. Hence, the present investigation is utilized to identify the volcanoes and their hotspot from the satellite images. Therefore to overcome the aforesaid problems, we are going to identify the hotspot of volcano using the Artificial Neural Network (ANN) which uses Resilient Back Propagation (RBP) Algorithm. At first, the color space of the satellite image will be converted to another color space to identify the contents of the image clearly. Then image will be segmented to identify the volcano's hotspot. To improve the accuracy, eight Statistical parameters are extracted from satellite image such as mean, variance, contrast, homogeneity, energy, correlation, standard deviation and entropy. The proposed mechanism will be developed with the aid of the platform MATLAB (version 7.11).

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Performance Analysis of Coiflets Wavelets for Segmentation of Heart Sound

Vol.1  No.4

Year : 2014

Issue : Oct-Dec

Title : Performance Analysis of Coiflets Wavelets for Segmentation of Heart Sound

Author Name : Lekram Premlal Bahekar, Sharadkumar Ghadale, Kiran Kawale, MAHENDRA BISEN

Synopsis : 

This paper discusses the usage of digital signal processing techniques on phonocardiography (PCG) waveforms and presents all the cardiac signals and their dates on the PC. This makes it easy for medical professionals to interpret disorders and make a better diagnosis. A segmentation which detects a single cardiac cycle (S1-Systole-S2-Diastole) of Phonocardiogram (PCG) signals using coiflets wavelet family and heart sound is classify into three types Normal (N), Systolic murmur (S) and Diastolic murmur (D). This paper proposed an adaptive sub-level tracking algorithm based on wavelet transform to separate the S1 and S2 from other components such as murmurs and noises Citerai of time interval, energy and phonocardiogram (PCG) collecting position which are used to identify S1 with respect to the beginning of each cardiac cycle. The pre-processing before calculating energy of PCG signal by wavelet, segments the PCG signal, and finds different parameters for segmentation. This paper presents an analysis of coiflets wavelet segmentation of heart sound segmentation techniques and suggested performance measures.

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Performance analysis of Anisotropic Diffusion filtering with Mathematical Morphology

Vol.1  No.4

Year : 2014

Issue : Oct-Dec

Title : Performance analysis of Anisotropic Diffusion filtering with Mathematical Morphology

Author Name : b sridhar, K.V.V.S.Reddy , A.M prasad

Synopsis : 

Mathematical Morphology is an efficient tool to extract the features from robust medical images. It provides a broad set of operations, which highlight the edges and improve the quality of the image. Anisotropic diffusion filtering has been widely applied as a mechanism for intra region smoothing of images. This paper aims to extend existing work in the development quality of medical image by using mathematical morphology and anisotropic vector gradient operators. Such types of operators may be anisotropic with respect to their shape and capacity to smooth the image locally as part of the feature extraction process. The proposed algorithm is applied on mammogram images. The performance of method is evaluated through peak signal to noise ratio, mean square error and structure similarity index measurement are calculated and plotted against the number of iterations of filter.

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A Review Of Intensity And Model Based Segmentation Methods For MRI

Vol.1  No.3

Year : 2014

Issue : Jul-Sep

Title : A Review Of Intensity And Model Based Segmentation Methods For MRI

Author Name : neela ramamoorthi, Kalai Magal R

Synopsis : 

Segmentation of various structures is a crucial step in the diagnosis and treatment of various diseases. Various imaging techniques such as X-ray, CT, (Computer Tomography), DTI (Diffusion Tensor Image), MRI (Magnetic Resonance Imaging), FMRI (Functional Magnetic Resource Imaging), PET (Positron Emission Tomography), SPECT (Single Photon Emission Computed Tomography), etc. are used in the treatment of diseases. Selection of the segmentation method depends on the modality used and the structures to be segmented. Accurate segmentation of various structures and computation of volume of tissues are required in the treatment of various diseases. In this paper, the authors present an overview of various segmentation techniques used in MRI analysis and their pros and cons. Also, the performance measures of some methods are evaluated.

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Comparison of PSNR Of DCT, DWT and DTT using Telenuclear Medical Image

Vol.1  No.3

Year : 2014

Issue : Jul-Sep

Title :  Comparison of PSNR Of DCT, DWT and DTT using Telenuclear Medical Image

Author Name :  HARATHI goud, Meenakshi V, Suneetha C H

Synopsis : 

The proliferation of digitized media due to the rapid growth of networked multimedia systems has created an urgent need for copyright enforcement technologies that can protect copyright. In this paper implementation of three different watermarking algorithms in the frequency domain is presented. The first algorithm is based on the Discrete Cosine Transform (DCT), the second one is based on the Discrete Wavelet Transform (DWT) and the third algorithm is based on the Discrete Tchebichef Transform (DTT).Embedding the watermark is done by modifying the coefficients of the middle frequency band so that the visibility of the image and diagnosis capability will not be affected. All schemes are tested using images and the simulation results are compared and the comparison shows the best scheme.

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Noise Minimization In Images Using Dual-Tree Complex Wavelet Transform

Vol.1  No.3

Year : 2014

Issue : Jul-Sep

Title :  Noise Minimization In Images Using Dual-Tree Complex Wavelet Transform

Author Name :  ARUNKUMAR M, leela rani

Synopsis :

This paper presents a novel way to reduce noise introduced by different image enhancement techniques. As the human visual system is highly sensitive to change in brightness, the proposed method is applied to the luma channel of both the non-enhanced and enhanced image. The basic assumption is that the non-enhanced image is either free of noise or noise is present but not perceivable. In order to avoid inappropriate assumptions on the statistical characteristics of noise, a different one is proposed. Also, it gives the importance of directional content in human vision and the analysis is performed through the Dual-Tree Complex Wavelet Transform (DTCWT). Compared to discrete wavelet transform, the DTCWT provides distinction of data directionality in the transform space. The standard deviation for each level of the transform of an non-enhanced image coefficients is computed and normalized across the six orientations of the DTWCT. The normalized said map is then used to shrink the coefficients of the enhanced image. The shrunk coefficients of the enhanced image are mixed according to data directionality, with the coefficients of non-enhanced image. Finally, the inverse transform provides the noise-reduced version. The proposed one thoroughly reduces the noise introduced by the enhancement methods and produces better improvement in PSNR of the image. In order to confirm the validity of the proposed method, a through numerical analysis of the results has been done.

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New Lifting Wavelets Based Medical Image Compression With Entropy Coding

Vol.1  No.3

Year : 2014

Issue : Jul-Sep

Title :  New Lifting Wavelets Based Medical Image Compression With Entropy Coding

Author Name :  Arikatla Hazarathaiah, B. Prabhakara Rao

Synopsis :

The main limitations on any communication system are “channel bandwidth” and “noise”. This paper deals with the data rate which is related to channel bandwidth. The real time images from any source will occupy large amount of space on a storage device. Hence it consumes maximum bandwidth for transmitting it and there are so many methods to reduce the image size and hence the bandwidth of the signal. This paper shows wavelet based compression methods. Discrete Wavelet Transform is a powerful tool for analyzing the signals. With the help of a thresholding function, it will be more useful in compression, but this method has some disadvantages like selectivity and shift invariance. So a much better method is proposed. In the proposed method a completely new set of wavelets were designed with lifting filters. Arithmetic coding is combined with proposed algorithm for reducing the size of images with less mean square error (MSE) at high compression ratio (CR).

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