本文選題：車輛檢測　切入點：暗通道　出處：《華南理工大學》2014年碩士論文

【摘要】：伴隨著交通管理系統(tǒng)越來越自動化、智能化，智能交通管理系統(tǒng)已經成為研究的熱點，車輛的檢測和跟蹤是智能交通管理系統(tǒng)的核心模塊，，其涵蓋了視頻監(jiān)控、計算機視覺技術、計算機圖像處理、機器學習以及許多其他領域的技術�？煽坑志哂袑崟r性的車輛檢測和跟蹤算法需要處理好背景變化、光線變化、陰影、目標遮擋等問題。關于車輛檢測和跟蹤算法，前人們已經提出了很多思路，但是要有效設計一個兼顧魯棒性和實時性的車輛檢測和跟蹤算法依然是一項很具有挑戰(zhàn)性的任務。基于此，本文對車輛檢測和跟蹤技術作了一定的探究和改進。 本文在車輛檢測部分，首先用混合高斯模型提取運動的目標，由于場景的復雜變化，使用混合高斯模型檢測的結果不理想，陰影的存在嚴重影響著檢測的效果，為此，本文根據陰影圖的反相圖具有類似半透明薄霧的性質，同時結合經典的去霧算法，提出了一種基于暗通道的陰影消除算法，該算法可以有效的消除車輛的陰影，并且對深色車輛的陰影也具有很好的魯棒性，從而可以更加精準地提取車輛的輪廓區(qū)域。在車輛跟蹤部分，本文提出了一種基于最大重疊面積和cam-shift的車輛快速跟蹤算法，該算法能夠有效地解決車輛粘連和分裂問題，同時還保證了車輛跟蹤的正確性和實時性。最后，本文還依據車輛跟蹤的結果，對一些相關的交通事件進行檢測，研究了車輛檢測和跟蹤的實際應用價值。
[Abstract]:With the traffic management system becoming more and more automatic, intelligent, intelligent traffic management system has become a hot research, vehicle detection and tracking is the core module of the intelligent traffic management system, which covers the video surveillance.Computer vision technology, computer image processing, machine learning, and many other fields of technology.Reliable and real-time vehicle detection and tracking algorithms need to deal with background changes, light changes, shadows, target occlusion and other problems.As for vehicle detection and tracking algorithms, many ideas have been proposed, but it is still a challenging task to effectively design a vehicle detection and tracking algorithm that takes into account both robustness and real-time.Based on this, this paper makes some research and improvement on vehicle detection and tracking technology.In the part of vehicle detection, first of all, the mixed Gao Si model is used to extract the moving target. Because of the complex change of the scene, the result of the detection using the mixed Gao Si model is not ideal, and the existence of shadow seriously affects the effect of the detection.In this paper, a shadow cancellation algorithm based on dark channel is proposed according to the property that the inverse phase diagram of shadow map is similar to translucent mist, and combined with the classical de-fogging algorithm, which can effectively eliminate the shadow of vehicle.And it has good robustness to dark vehicle shadow, so it can extract the contour area of vehicle more accurately.In the part of vehicle tracking, a fast vehicle tracking algorithm based on maximum overlap area and cam-shift is proposed. The algorithm can effectively solve the problem of vehicle adhesion and splitting, and ensure the correctness and real-time of vehicle tracking.Finally, based on the results of vehicle tracking, some related traffic events are detected, and the practical application value of vehicle detection and tracking is studied.
【學位授予單位】：華南理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U495

【參考文獻】

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本文編號：1701664