Informatics Publishing Limited

K. Vidyavathi ¹, R. S. Sabeenian ²

Affiliations
1 Department of Electronics and Communication Engineering, King College of Technology, Nallur, Pudupatti (PO), Namakkal-637020, IN
2 Sona Signal and Image Processing (SONA-SIPRO) Laboratory, Sona College of Technology, Salem-636005, IN

Abstract

Generally, the resolution of the TV image is increased for HDTV. In the present HDTV systems only the spatial resolution is increased, without simultaneously increasing the frame rate for improved temporal resolution. This can lead to disappointing results for TV applications, where movement is important. Therefore it is important to consider the motion effects of the HD video signals. The recent LCD panels suffered by the slow response and hold effect, which are the hidden limitations that will degrade the performance of the system.
By considering an additional set of predictors, improving the thresholding process, and simplifying the search pattern employed by these algorithms, we not only manage in achieving better output quality, but also reduce complexity of the motion estimation process even further. Our algorithm was compared with the algorithms accepted in the Optimization Model 1.0 of MPEG-4, and our simulations prove its outright superiority versus the existing algorithms.
In this paper, the estimation of total motion based on absolute differences between frames in a block of video, without respect to the direction of motion that causes differences.

Keywords

HDTV, Motion Estimation, Motion Compensation, Video Compression, Block Motion.

Full Text

     

R. S. Sabeenian ¹

Affiliations
1 Department of Electronics & Communication Engineering, Sona SIPRO (Sona Signal and Image Processing) Research Centre, Sona College of Technology, Salem-636005, IN

Abstract

Tea Industries in turn process the tea leaves for exporting the tea production. Quality of the tea is very important. However tea color determination during fermentation is a vital problem in the tea industries. This makes a major contribution of the quality of tea. The human experts since the beginning of the tea industry have been traditionally measuring tea color and flavor to detect the optimum fermenting condition. They use visual inspection and smelling or tasting method which is purely subjective, invasive, time consuming and inexact due to various reasons such as individual variability, adaptation, infection, mental state etc. Chemical analysis is also performed on the tea leaves to determine the fermentation condition. This in turn degrades the quality of the tea. The grading of the tea also differs. Also whenever the leaves are fermented more, they are not used for exporting and hence there is more wastage in the processing. Hence we implement non-destructive testing of tea leaves by using image processing technique. The proposed Multi Resolution Statistical Markov Random Field Matrix (MRSMRFM) method is a combination of first order and second order statistical and spectral features used to test and determine the optimal fermenting condition.

Keywords

Texture, Tea Leaves, Wavelet Transform, Markov Random Field (MRF), Gray Level Co Occurrence Method (GLCM), Multi Resolution Statistical Markov Random Field Matrix (MRSMRFM).

Full Text

     

R. S. Sabeenian ¹, S. Boopathy ²

Affiliations
1 ECE Department, Sona College of Technology, Salem, Tamil Nadu, IN
2 Sona College of Technology, Salem, Tamil Nadu, IN

Abstract

Grapes are a crop that is susceptible to many diseases. However, the degree of susceptibility varies depending on the variety. When no pest management is carried out, damage can generally be severe. Downy mildew and powdery mildew are the major grape diseases in India. Evidently, these diseases can be easily predicted based on the climatic conditions determined by agricultural experts. Technological strategies using machine vision and artificial intelligence are being investigated to achieve intelligent farming forbetter yield. As a part of the prediction process in Grapes, this paper initially deals with the identification of type of disease that has occurred in a grape vine, with a special focus on its leaves. The first step in an effective pest management program is correct identification of the disease. This paper uses GLCM (Gray Level Co-occurrence Matrix) and Wavelet statistical Features to determine whether a given grape leaf is affected with Powdery Mildew or Downy Mildew by comparing the statistical features with that of an unaffected leaf. The developed algorithm's efficiency can successfully detect and classify the examined diseases with a precision of 94%.

Keywords

Grapes, GLCM (Gray Level Co-Occurrence Matrix), Wavelet Transform, Color Thresholding Powdery Mildew and Downy Mildew and Wavelet Statistical Features.

Full Text

     

M. Varathaguru ¹, R. S. Sabeenian ²

Affiliations
1 Electronics and Communication Engineering Department, Government Polytechnic College Coimbatore-641014 Tamilnadu, IN
2 Electronics and Communication Engineering Department, Sona College of Technology Salem-636005, Tamilnadu, IN

Abstract

This paper studies image compression using SPIHT and Modified SPIHT algorithm. Image compression is one of the important applications in data compression on its image. Image data requires huge amount of disk space and large bandwidths for transmission. Hence, image compression is necessary to reduce the amount of data required to represent digital image.Discrete Wavelet Transform (DWT) based image compression has been paid much attention in the past decades. DWT has been adopted as a new technical standard for still image compression. Set Partitioning in Hierarchical Trees (SPIHT) is the DWT-based image compression algorithm which is more powerful, efficient and more popular, due to the properties of fast computation, low memory requirement. Discrete wavelet transform (DWT) based Set Partitioning in Hierarchical Trees (SPIHT) algorithm is widely used in many image compression systems.In this paper an attempt has been made to study the performance of Set partition in Hierarchical Tree (SPIHT) and modified SPIHT algorithms for image compression. In addition to evaluate the performance of SPIHT algorithm with Modified SPIHT, it has given reduced scan redundancy and bit redundancy.

Keywords

Discrete Wavelet Transform (DWT), Image Compression, SPIHT and Modified SPIHT.

Full Text

     

P. Anandan ¹, R. S. Sabeenian ²

Affiliations
1 Department of Electronics and Communication Engineering, Sengunthar Engineering College, Tiruchengode-637 205, Tamilnadu, IN
2 Department of Electronics and Communication Engineering, Sona College of Technology, Salem-636 005 Tamilnadu, IN

Abstract

Image processing holds a very important role in various application fields such as medical, education, surveillance etc. Images are very important documents nowadays; to work with them in some applications they need to be compressed, more or less depending on the purpose of the application. Many different image compression techniques currently exist for the compression of different types of images. Image compression is fundamental to the efficient and cost-effective use of digital imaging technology and applications. An investigation is done on the various types of image compression techniques that exist. This paper deals with study of different available image compression techniques with their performance results.

Keywords

Image Compression, Curvelet Transform, Contourlet Transform, Ridgelet Transform, Fractal Transform.

Full Text

     

M. E. Paramasivam ¹, R. S. Sabeenian ¹, P. M. Dinesh ¹

Affiliations
1 Department of Electronics and Communication Engineering, Sona College of Technology, IN

Abstract

Color-to-Gray scale conversion methods try to identify weights for various color channels to obtain a gray-scale image. These weights can be fixed either globally or computed on a localized basis. This paper presents an approach for computing the global weights using localized regions perpetually selected based on human perception. The approach aims to bring forth a color invariant gray scale conversion, such that it tries to maximize the required foreground information. The proposed method was tested on DIBCO-2013 dataset and qualitatively evaluated by looking at the structural similarity with the foreground using SSIM. The experimental results of ours and other color-to-gray scale methods have been tabulated and discussed.

Keywords

Color-to-Grayscale Conversion, Multiple Regression, Least-Square Approach, Color Image, Gray Scale Image.

Full Text

     

T. Shanthi ¹, R. S. Sabeenian ¹, K. Manju ¹, M. E. Paramasivam ¹, P. M. Dinesh ¹, R. Anand ¹

Affiliations
1 Department of Electronics and Communication Engineering, Sona College of Technology, IN

Abstract

We find the usefulness of computers in every field including medical field. Scanning the affected part has become a standard study. Diagnosing a disease at the right time, i.e. early detection, from the study of images enables the physician to take right decision and provide proper treatment to the patient. With the alarming growth of population, it is difficult for every individual patient to get a second opinion from medical expert. In these situations, computer-aided automatic diagnosis system will be much helpful. Diabetic retinopathy is a disorder that arises from increase in blood glucose level. Based on the severity, it has been distinguished into four stages. Diagnosing diabetic retinopathy at an early stage from retinal images and providing proper treatment will save the patient from severe vision loss. The proposed method adopts hybridized GLCM features and wavelet features to classify the fundus images according to the severity of the disease. The method is tested with fundus images collected from Indian Diabetic Retinopathy Dataset.

Keywords

Fundus Image, GLCM, WDM Features, Diabetic Retinopathy, Classification.

Full Text