Comparison of Leaf Recognition by Moments and Fourier Descriptors
نویسندگان
چکیده
We test various features for recognition of leaves of wooden species. We compare Fourier descriptors, Zernike moments, Legendre moments and Chebyshev moments. All the features are computed from the leaf boundary only. Experimental evaluation on real data indicates that Fourier descriptors slightly outperform the other tested features.
منابع مشابه
Vision Based Multi-feature Hand Gesture Recognition for Indian Sign Language Manual Signs
Indian sign language (ISL) is the main communication medium among deaf Indians. An ISL vocabulary show that the hand plays a significant role in ISL. ISL includes static and dynamic hand gesture recognition. The main aim of this paper is to present multi-feature static hand gesture recognition for alphabets and numbers. Here, comparative analysis of various feature descriptors such as chain cod...
متن کاملQuaternion Bessel-Fourier moments and their invariant descriptors for object reconstruction and recognition
In this paper, the quaternion Bessel-Fourier moments are introduced. The significance of phase information in quaternion Bessel-Fourier moments is investigated and an accurate estimation method for rotation angle is described. Furthermore, a new set of invariant descriptors based on the magnitude and the phase information of quaternion Bessel-Fourier moments is derived. Experimental results sho...
متن کاملA complex network-based approach for boundary shape analysis
This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a Small World complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has an efficient power of shape characterization, it is robust, noise tolerant, scale invariant and ...
متن کاملComparison of Shape Descriptors for Mice Behavior Recognition
Shape representation provides fundamental features for many applications in computer vision and it is known to be important cues for human vision. This paper presents an experimental study on recognition of mice behavior. We investigate the performance of the four shape recognition methods, namely Chain-Code, Curvature, Fourier descriptors and Zernike moments. These methods are applied to a rea...
متن کاملPattern Recognition and feature extraction: a comparative study
The selection of features for classifying a pattern by means a fuzzy reasoning, is fundamental in order to obtain a reliable and significative response. The scope of this work is to compare three methods specialized for the extraction of features from images and, consequently, to study the ability of classification performed by applying a fuzzy inference system. The methods to be compared were:...
متن کامل