Editorial Board of American Journal of Computer Engineering
Dept. of Computer Science and Engineering
Cvr college of engineering, Hyderabad
Biography & Research Interest
Welcome Dr. G.N.Balaji to Join the Editorial Board of American Journal of Computer Engineering.
Personal Skill Set
Quick & Self Learner – Most of the computer skill sets mentioned below are self-learned.
Designer/Developer – I love to design/develop things from scratch.
Good Analytical skills – Ability to analyse a problem and devise suitable solution.
Can do Attitude – My can do attitude developed over the time had helped tackle difficult problems.
Computer Skill Sets
Tools MATLAB, OpenCV, Latex
Languages C, C++, Java, HTML 5
Skills Image Processing and Computer Vision.
Academic Projects –
B.E: Retinal Blood Vessel Segmentation
Proposed an automated method for the segmentation of the vascular network in retinal images. The algorithm starts with the extraction of vessel centerlines, which are used as
guidelines for the subsequent vessel filling phase.
For this purpose, the outputs of four directional differential operators are processed in order to select connected sets of candidate points to be further classified as centerline pixels using vessel derived features
The final segmentation is obtained using an iterative region growing method that integrates the contents of several binary images resulting from vessel width dependent morphological
The results demonstrate that our algorithm outperforms other solutions and approximates the average accuracy of a human observer without a significant degradation of sensitivity and specificity.
M.Tech: Ontology Concepts for Requirements Engineering Process in E- Government
Proposed ontology concept in the domain of requirements engineering process for E-gov applications.
This contributes in enabling software engineers to find out shared-understandable and common concepts to describe requirements for different domain models used in developing E-gov applications.
Several documents related to E-gov requirement are collected; the main concepts and relationships are extracted and refined.
The main theme to provide common concepts and understanding of the requirements for many E-gov applications.
Ph.D: Automatic Detection and Diagnosis of Cardiac Abnormalities
An approach for heart muscle damage detection from echocardiography sequences is proposed.
To exemplify the approach, a system is presented which involves image denoising and enhancement and segmentation of the left ventricle (LV) for extracting the heart wall boundaries.
Using the heart wall boundaries global LV parameters are calculated followed by statistical pattern recognition and classification to identify the heart muscle damage or myocardial ischemia (MI).
The experimental results reveal that the proposed method can be used as an effective tool for detection of heart muscle damage or MI automatically.
Coordinator – UGC sponsored Innovative Research Project
Computer aided Detection and Diagnosis of diaphysis femur fracture
Classification of the antero-posterior and lateral x- ray views.
Classification the Normal and diaphysis femur fracture in both views.
Classification type of fracture ie., Spiral, Comminuted or Transverse and
Report generation by combining the results in both views.
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