Proceeding of

NCAICN National Conference 2013

(NCAICN-2013)

on

Advances in

Computing & Networking

as

A Special Issue of

International Journal of Computer Science and Applications

(ISSN:0974-1011)

Patron

Hon. Shri Sundeepji Meghe

(Chairman, Vidarbha Youth Welfare Society, Amravati)

 

Advisor

Dr. V.T. Ingole (FIE, FIETE, Professor Emeritus)

 

Organizing Committee

Chairman

Dr. D.T. Ingole (FIE, FIETE)

(Principal PRMIT & R, Badnera and  Chairman IEI  Amravati Center).

Secretary

 Er. A.W. Jawanjal

(Honorary Secretary IEI, Amravati Center)

Conveners

Dr. G.R. Bamnote ((FIE, FIETE)

(H.O.D. Computer Science & Engineering)

Dr. A.S. Alvi (MIE)

(H.O.D. Information Technology))

Prof. Mrs. M.D. Ingole (FIE.MIETE)

(H.O.D. Electronics & Telecommunication)

Coordinators

Prof. S.V. Dhopte ((FIE, FIETE)

Prof. Ms. V.M. Deshmukh (FIE, FIETE)

Dr. S.W. Mohod  (FIE,FIETE)

Co-Coordinators

Dr. S.R. Gupta (MIE, MIETE)

Prof. S.V. Pattalwar ((FIE, FIETE)

Prof. M.D. Damahe

Members

Prof. Mrs. M.S. Joshi                

Dr. S.M. Deshmukh

Prof. V.U. Kale

Prof. S.S. Kulkarni

Prof. Ms. R.R. Tuteja

Prof. Ms. J.N. Ingole

Prof. V.R. Raut

Prof. C.N. Deshmukh

Prof. Ms. M.S. Deshmukh

Prof. S.P. Akarte

Prof. Mrs. A.P. Deshmukh

Prof. Mrs. S.S. Sikchi

Prof. N.N. Khalsa

Department of Information and Computer Science and Engineering

Prof. Ram Meghe Institute of Technology and Research, Badnera Distt. Amravati

 

Editor

Prof. K. H. Walse

M.S.India

 

 

 

   
   
   
   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
IJCSA ISSN: 0974-1011 (Online) >>    
Title:

Object Detection and Recognization by Image Parsing using Matlab Wavelet Technique

Author:
Shrikant N. Sarda, Dr. V.T.Ingole and Prof. V.K.Patil
 

Abstract

These systems propose a general framework for parsing images into regions and objects. In this framework, the detection and recognition of objects proceed simultaneously with image segmentation in a competitive and cooperative manner. This approach illustrates natural images of complex city scenes where the objects of primary interest are faces and text. This method makes use of bottom-up proposals combined with top-down generative models algorithm which is guaranteed to converge to the optimal estimate asymptotically. More precisely, it is define generative models for faces, text, and generic regions– e.g. shading, texture, and clutter. These models are activated by bottom-up proposals. This system illustrate the advantages and importance of combining bottom-up and Top-down models and of performing segmentation and object detection/recognition simultaneously.



©2013 International Journal of Computer Science and Applications 

Published by Research Publications, India