Three Dimensional Object Recognition using PCA and KNN

نویسندگان

چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Object recognition using three-dimensional optical quasi-correlation.

A novel method of three-dimensional (3-D) object recognition is proposed. Several projections of a 3-D target are recorded under white-light illumination and fused into a single complex two-dimensional function. After proper filtering, the resulting function is coded into a computer-generated hologram. When this hologram is coherently illuminated, a correlation space is reconstructed such that ...

متن کامل

Three-Dimensional Object Recognition: Statistical Approach

The design of a general purpose artificial vision system capable of recognizing arbitrarily complex threedimensional objects without human intervention is still a challenging task in computer vision. Experiments have been conducted to test the ability of incorporating the knowledge of how human vision system works in a threedimensional object recognition system. Firstly, the process of shape ou...

متن کامل

Face Recognition using Eigenfaces , PCA and Supprot Vector Machines

This paper is based on a combination of the principal component analysis (PCA), eigenface and support vector machines. Using N-fold method and with respect to the value of N, any person’s face images are divided into two sections. As a result, vectors of training features and test features are obtain ed. Classification precision and accuracy was examined with three different types of kernel and...

متن کامل

3D Face Recognition based on Radon Transform, PCA, LDA using KNN and SVM

Biometrics (or biometric authentication) refers to the identification of humans by their characteristics or traits. Bio-metrics is used in computer science as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance. Biometric identifiers are the distinctive, measurable characteristics used to label and describe individuals. Thre...

متن کامل

Face Representation And Recognition Using Two-Dimensional PCA

In this paper, two-dimensional principal component analysis (2DPCA) is used for image representation and recognition. Compared to 1D PCA, 2DPCA is based on 2D image matrices rather than 1D vectors so the image matrix does not need to be transformed into a vector prior to feature extraction. Instead, an image covariance matrix is constructed directly using the original image matrices, and its ei...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: The Journal of the Korea Contents Association

سال: 2009

ISSN: 1598-4877

DOI: 10.5392/jkca.2009.9.8.057