Detection Algorithm for Road Surface Condition using Wavelet Packet Transform and SVM

被引：0

作者：

Yang, Hun-Jun ^{[1
]}

Jang, Hyeok ^{[1
]}

Jeong, Dong-Seok ^{[1
]}

机构：

[1] Inha Univ, Multimedia Lab, Inchon, South Korea

来源：

PROCEEDINGS OF THE 19TH KOREA-JAPAN JOINT WORKSHOP ON FRONTIERS OF COMPUTER VISION (FCV 2013) | 2013年

关键词：

Texture classification; Wavelet Packet Transform; Support Vector Machine;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose a method to detect the state of the road surface condition using wavelet and SVM(Support Vector Machine) classifier. The Road surface conditions are classified into a set of pattern states such as dry, wet, snow, ice. This approach automatically analyze road surface condition change using image processing, and does not require extra sensors. Feature extraction using wavelet transformation is classified by the SVM classifier.

引用

页码：323 / 326

页数：4

共 8 条

[1]

Abe S., 2005, ADV PTRN RECOGNIT

[2]

[Anonymous], 2000, IEEE T SYSTEMS MAN C

[3] On the optimality of the simple Bayesian classifier under zero-one loss [J].

Domingos, P ;

Pazzani, M .

MACHINE LEARNING, 1997, 29 (2-3) :103-130

[4]

Fukunaga K, 1990, INTRO STAT PATTERN R, V2nd

[5]

Gonzalez R.C., 2008, Digital Image Processing, V3rd

[6]

Im S.H., 2007, ROAD SURFACE DETECT

[7]

Oh I. S., 2010, PANTTERN RECOGNITION

[8] VARIABLE KERNEL DENSITY-ESTIMATION [J].

TERRELL, GR ;

SCOTT, DW .

ANNALS OF STATISTICS, 1992, 20 (03) :1236-1265

← 1 →