Leaf recognition using contour based edge detection and SIFT algorithm

The paper presents two advanced methods for comparative study in the field of computer vision. The first method involves the implementation of the Scalar Invariant Fourier Transform (SIFT) algorithm for the leaf recognition based on the key descriptors value. The second method involves the contour-b...

Full description

Saved in:
Bibliographic Details
Published in2014 IEEE International Conference on Computational Intelligence and Computing Research pp. 1 - 4
Main Authors Lavania, Shubham, Matey, Palash Sushil
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2014
Subjects
Accuracy
Classification algorithms
Computer vision
contour-based corner detector
corner detection
Detectors
Feature extraction
Image edge detection
leaf recognition
mean projection transform
SIFT
Online AccessGet full text
ISBN1479939749
9781479939749
DOI10.1109/ICCIC.2014.7238345

Cover

More Information
Summary:The paper presents two advanced methods for comparative study in the field of computer vision. The first method involves the implementation of the Scalar Invariant Fourier Transform (SIFT) algorithm for the leaf recognition based on the key descriptors value. The second method involves the contour-based corner detection and classification which is done with the help of Mean Projection algorithm. The advantage of this system over the other Curvature Scale Space (CSS) systems is that there are fewer false-positive (FP) and false-negative (FN) points compared with recent standard corner detection techniques. The performance analysis of both the algorithm was done on the flavia database.
ISBN:1479939749
9781479939749
DOI:10.1109/ICCIC.2014.7238345