计算机工程
計算機工程
계산궤공정
COMPUTER ENGINEERING
2014年
9期
210-214
,共5页
车辆检测%误检%方向梯度直方图%局部二进制模式%主成分分析%支持向量机
車輛檢測%誤檢%方嚮梯度直方圖%跼部二進製模式%主成分分析%支持嚮量機
차량검측%오검%방향제도직방도%국부이진제모식%주성분분석%지지향량궤
vehicle detection%erroneous inspection%Histogram of Oriented Gradient ( HOG )%Local Binary Pattern ( LBP)%Principal Component Analysis( PCA)%Support Vector Machine( SVM)
针对形状特征在车辆检测中存在的误检现象,在分析误检原因的基础上,提出一种融合形状和纹理特征的车辆检测方法。对检测窗口中划分的胞元进行方向梯度直方图特征和统一化局部二进制模式算子的求解,统计检测窗口中各胞元的特征情况,在形成浏览窗口的形状和纹理特征过程中,采用主成分分析解决特征的高维度和冗余问题,结合支持向量机进行特征训练和检测实验。实验结果证明,该方法有效兼顾车辆图像的形状和纹理两方面的特征,在不影响检测速度的同时,明显降低了车辆检测的误检率,在时效和精度两方面都取得较好的效果。
針對形狀特徵在車輛檢測中存在的誤檢現象,在分析誤檢原因的基礎上,提齣一種融閤形狀和紋理特徵的車輛檢測方法。對檢測窗口中劃分的胞元進行方嚮梯度直方圖特徵和統一化跼部二進製模式算子的求解,統計檢測窗口中各胞元的特徵情況,在形成瀏覽窗口的形狀和紋理特徵過程中,採用主成分分析解決特徵的高維度和冗餘問題,結閤支持嚮量機進行特徵訓練和檢測實驗。實驗結果證明,該方法有效兼顧車輛圖像的形狀和紋理兩方麵的特徵,在不影響檢測速度的同時,明顯降低瞭車輛檢測的誤檢率,在時效和精度兩方麵都取得較好的效果。
침대형상특정재차량검측중존재적오검현상,재분석오검원인적기출상,제출일충융합형상화문리특정적차량검측방법。대검측창구중화분적포원진행방향제도직방도특정화통일화국부이진제모식산자적구해,통계검측창구중각포원적특정정황,재형성류람창구적형상화문리특정과정중,채용주성분분석해결특정적고유도화용여문제,결합지지향량궤진행특정훈련화검측실험。실험결과증명,해방법유효겸고차량도상적형상화문리량방면적특정,재불영향검측속도적동시,명현강저료차량검측적오검솔,재시효화정도량방면도취득교호적효과。
According to the feature erroneous inspection that consists in vehicle detection,this paper proposes a vehicle detection method based on the fusion shape and texture characteristics in analysis of the error reason. It calculates the Histogram of Oriented Gradient ( HOG ) feature and the unified Local Binary Pattern ( LBP ) operator for all cell in detection window,solves the problem of high dimension characteristic and redundancy by Principal Component Analysis ( PCA) in the browser window and texture characteristics-forming process. Combined with the Support Vector Machine ( SVM) ,it does the feature training and test experiment. Experimental results show that this method juggles both sides of the shape and texture characteristics in vehicle image effectively,significantly reduces the error probability of the vehicle detection when meets the detection speed,gets good effect both in efficiency and accuracy.