中国机械工程
中國機械工程
중국궤계공정
CHINA MECHANICAl ENGINEERING
2014年
20期
2825-2829
,共5页
自动泊车%视觉%车位线识别%金字塔分层%图像匹配
自動泊車%視覺%車位線識彆%金字塔分層%圖像匹配
자동박차%시각%차위선식별%금자탑분층%도상필배
automatic parking%vision%parking slot marking recognition%pyramid delamination%im-age matching
提出了一种自动泊车系统中采用视觉方法通过识别车位线来确定泊车位的算法。采用金字塔分层搜索策略,首先,在灰度直方图上应用K均值聚类法对图像进行二值化,提取车位线骨架,采用Hough变换检测骨架,并利用基于密度的无参数聚类方法对骨架线聚类,在金字塔高层图像上确定车位角点候选点;然后,在金字塔最底层图像上选择感兴趣区域,采用改进的基于距离变换的骨架提取算法提取骨架,使用遗传算法对车位角点骨架进行精确匹配,根据实际车位角点的分布特征确定目标车位;最后,在室外不同环境下采集多张车位图片进行算法的有效性和快速性验证实验。实验结果表明,采用基于视觉的车位线识别算法进行车位检测能较大地提高检测的效率和识别正确率。
提齣瞭一種自動泊車繫統中採用視覺方法通過識彆車位線來確定泊車位的算法。採用金字塔分層搜索策略,首先,在灰度直方圖上應用K均值聚類法對圖像進行二值化,提取車位線骨架,採用Hough變換檢測骨架,併利用基于密度的無參數聚類方法對骨架線聚類,在金字塔高層圖像上確定車位角點候選點;然後,在金字塔最底層圖像上選擇感興趣區域,採用改進的基于距離變換的骨架提取算法提取骨架,使用遺傳算法對車位角點骨架進行精確匹配,根據實際車位角點的分佈特徵確定目標車位;最後,在室外不同環境下採集多張車位圖片進行算法的有效性和快速性驗證實驗。實驗結果錶明,採用基于視覺的車位線識彆算法進行車位檢測能較大地提高檢測的效率和識彆正確率。
제출료일충자동박차계통중채용시각방법통과식별차위선래학정박차위적산법。채용금자탑분층수색책략,수선,재회도직방도상응용K균치취류법대도상진행이치화,제취차위선골가,채용Hough변환검측골가,병이용기우밀도적무삼수취류방법대골가선취류,재금자탑고층도상상학정차위각점후선점;연후,재금자탑최저층도상상선택감흥취구역,채용개진적기우거리변환적골가제취산법제취골가,사용유전산법대차위각점골가진행정학필배,근거실제차위각점적분포특정학정목표차위;최후,재실외불동배경하채집다장차위도편진행산법적유효성화쾌속성험증실험。실험결과표명,채용기우시각적차위선식별산법진행차위검측능교대지제고검측적효솔화식별정학솔。
An algorithm was proposed herein for an automatic parking system ,which used vision for recognition of parking slot marking .Pyramid hierarchical search strategy was adopted .First ,image binarization was carried out by applying K means clustering to the intensity histogram and skeleton of parking slot marking was extracted .Parking space corner candidate point was determined in high-level pyramid image using Hough transform to detect skeleton and skeleton clustered using unsupervised cluster based on density .Then ,region of interest was seleted in lowest -level pyramid image and skel-eton was extracted using improved distance transform-based skeleton extraction algorithm .Skeleton of parking space corner was matched using genetic algorithm and target parking space was determined according to characteristics of actual parking space .Lastly ,the effectiveness and rapidity of the pro-posed algorithm was verified by collecting many parking space images in the outdoor environment .Ex-perimental results demonstrate that computation is small and parking recognition accuracy is as 98%using the proposed algorithm .