Name
Title | ||
|---|---|---|
Classification of fruits using computer vision and a multiclass support vector machine. |
Abstract | ||
|---|---|---|
Automatic classification of fruits via computer vision is still a complicated task due to the various properties of numerous types of fruits. We propose a novel classification method based on a multi-class kernel support vector machine (kSVM) with the desirable goal of accurate and fast classification of fruits. First, fruit images were acquired by a digital camera, and then the background of each image was removed by a split-and-merge algorithm; Second, the color histogram, texture and shape features of each fruit image were extracted to compose a feature space; Third, principal component analysis (PCA) was used to reduce the dimensions of feature space; Finally, three kinds of multi-class SVMs were constructed, i.e., Winner-Takes-All SVM, Max-Wins-Voting SVM, and Directed Acyclic Graph SVM. Meanwhile, three kinds of kernels were chosen, i.e., linear kernel, Homogeneous Polynomial kernel, and Gaussian Radial Basis kernel; finally, the SVMs were trained using 5-fold stratified cross validation with the reduced feature vectors as input. The experimental results demonstrated that the Max-Wins-Voting SVM with Gaussian Radial Basis kernel achieves the best classification accuracy of 88.2%. For computation time, the Directed Acyclic Graph SVMs performs swiftest. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.3390/s120912489 | SENSORS |
Keywords | Field | DocType |
fruit classification,principal component analysis,color histogram,Unser's texture analysis,mathematical morphology,shape feature,multi-class SVM,kernel SVM,stratified cross validation | Computer vision,Feature vector,Pattern recognition,Least squares support vector machine,Radial basis function kernel,Kernel embedding of distributions,Support vector machine,Kernel principal component analysis,Polynomial kernel,Artificial intelligence,Engineering,Kernel method | Journal |
Volume | Issue | ISSN |
12 | 9.0 | 1424-8220 |
Citations | PageRank | References |
36 | 1.56 | 13 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| yudong zhang | 1 | 1334 | 90.44 |
| Lenan Wu | 2 | 700 | 62.18 |