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Analysis of two dimensional image to obtain unique statistical features for developing image recognition techniques using wavelet approach

Authors:

A. K. Dubey,

A. Q. Ansari,

R. P. SinghAuthors Info & Claims

ICWET '11: Proceedings of the International Conference & Workshop on Emerging Trends in Technology

Pages 66 - 70

https://doi.org/10.1145/1980022.1980036

Published: 25 February 2011 Publication History

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Abstract

The Wavelets are mathematical functions. They are used to catch up the data into different frequency components and study the components with a resolution matched to its scale. Wavelets were developed for the fields of mathematics, modern physics, electrical and electronics engineering, and seismic geology. The remarkable developments is being observed in these fields during the last 15 years and have led to many new wavelet applications such as image compression, de-noising, computer vision, automation, automatic visual inspection systems, turbulence, human vision, radar, and earth quake prediction etc. The proposed methodology provides an approach for exploring unique statistical information contained in 2D images, which may further be utilized for developing image recognition techniques.

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Yogesh Dubey A(2016)Fruit defect detection based on speeded up robust feature technique2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)10.1109/ICRITO.2016.7785023(590-594)Online publication date: Sep-2016
https://doi.org/10.1109/ICRITO.2016.7785023
Ansari AKour J(2015)Uniform segmentation in online signature verification2015 Annual IEEE India Conference (INDICON)10.1109/INDICON.2015.7443278(1-6)Online publication date: Dec-2015
https://doi.org/10.1109/INDICON.2015.7443278
Jaffery ZDubey A(2013)Architecture of Noninvasive Real Time Visual Monitoring System for Dial Type Measuring InstrumentIEEE Sensors Journal10.1109/JSEN.2012.223194013:4(1236-1244)Online publication date: Apr-2013
https://doi.org/10.1109/JSEN.2012.2231940

Analysis of two dimensional image to obtain unique statistical features for developing image recognition techniques using wavelet approach
1. Computing methodologies
  1. Artificial intelligence
  2. Computer graphics
2. Mathematics of computing
  1. Mathematical analysis
    1. Numerical analysis

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ICWET '11: Proceedings of the International Conference & Workshop on Emerging Trends in Technology

February 2011

1385 pages

ISBN:9781450304498

DOI:10.1145/1980022

Program Chair:
B. K. Mishra

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 25 February 2011

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Thakur College Of Engg. & Tech

ICWET '11: International Conference & Workshop on Emerging Trends in Technology

February 25 - 26, 2011

Maharashtra, Mumbai, India

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Yogesh Dubey A(2016)Fruit defect detection based on speeded up robust feature technique2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO)10.1109/ICRITO.2016.7785023(590-594)Online publication date: Sep-2016
https://doi.org/10.1109/ICRITO.2016.7785023
Ansari AKour J(2015)Uniform segmentation in online signature verification2015 Annual IEEE India Conference (INDICON)10.1109/INDICON.2015.7443278(1-6)Online publication date: Dec-2015
https://doi.org/10.1109/INDICON.2015.7443278
Jaffery ZDubey A(2013)Architecture of Noninvasive Real Time Visual Monitoring System for Dial Type Measuring InstrumentIEEE Sensors Journal10.1109/JSEN.2012.223194013:4(1236-1244)Online publication date: Apr-2013
https://doi.org/10.1109/JSEN.2012.2231940

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Image compression using shift-invariant dyadic wavelets

Analysis of Multispectral Image Using Discrete Wavelet Transform

A New Image Denoising Method Using Wavelet Transform

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