本文選題：運(yùn)動(dòng)檢測(cè) + 背景更新策略�。� 參考：《西安理工大學(xué)》2017年碩士論文

【摘要】：人們常說(shuō)“眼睛是心靈的窗戶”。因?yàn)橄忍旎蚝筇煸?成千上萬(wàn)人的無(wú)法看到世界。盲人的日常生活受到很多限制,如行走時(shí)無(wú)法及時(shí)察覺(jué)到危險(xiǎn),從而給盲人出行帶來(lái)嚴(yán)重問(wèn)題。隨著計(jì)算機(jī)技術(shù)和通信技術(shù)的高速發(fā)展,盲人輔助視覺(jué)設(shè)備快速發(fā)展,越來(lái)越多的科研人員致力于相關(guān)技術(shù)的研究。本文主要研究動(dòng)態(tài)目標(biāo)檢測(cè)和靜態(tài)目標(biāo)邊緣檢測(cè)兩個(gè)方面,完成以下工作:首先分析各種傳統(tǒng)的算法原理和適用場(chǎng)景,采用適用于盲人行走輔助的改進(jìn)算法,在動(dòng)態(tài)目標(biāo)檢測(cè)方面采用ViBe算法結(jié)合計(jì)數(shù)更新背景和計(jì)數(shù)重新初始化背景模型機(jī)制,在靜態(tài)目標(biāo)邊緣提取采用自適應(yīng)閾值方式。然后對(duì)改進(jìn)算法與傳統(tǒng)算法進(jìn)行MATLAB仿真,分別用F_Measure參數(shù)和主觀觀測(cè)兩種方式進(jìn)行比較,MATLAB結(jié)果表明,動(dòng)態(tài)目標(biāo)檢測(cè)改進(jìn)算法的召回率比原算法高10%,準(zhǔn)確率比原算法高6%,靜態(tài)目標(biāo)邊緣提取改進(jìn)算法可以有效提取感興趣邊緣信息,排除無(wú)效干擾;接著對(duì)改進(jìn)算法進(jìn)行Verilog硬件電路實(shí)現(xiàn),對(duì)硬件電路進(jìn)行ModelSim仿真分析;最后搭建目標(biāo)檢測(cè)系統(tǒng),從攝像頭配置到VGA顯示,在開(kāi)發(fā)板上驗(yàn)證整體系統(tǒng)的處理效果。將硬件實(shí)現(xiàn)結(jié)果與MATLAB處理結(jié)果做對(duì)比,硬件處理結(jié)果相比于軟件處理結(jié)果在像素點(diǎn)處最大相對(duì)誤差為4. 3%,硬件實(shí)現(xiàn)達(dá)到設(shè)計(jì)要求。論文目標(biāo)檢測(cè)實(shí)驗(yàn)結(jié)果表明:動(dòng)態(tài)目標(biāo)檢測(cè)結(jié)合ViBe算法與計(jì)數(shù)更新背景模型和計(jì)數(shù)重新初始化背景模型策略可以更適應(yīng)于運(yùn)動(dòng)場(chǎng)景的目標(biāo)檢測(cè);靜態(tài)目標(biāo)邊緣檢測(cè)采用自適應(yīng)閾值可以減少無(wú)關(guān)信息的干擾。將目標(biāo)檢測(cè)通過(guò)硬件電路實(shí)現(xiàn),更好滿足了實(shí)時(shí)性要求,豐富了視覺(jué)假體中圖像處理的研究?jī)?nèi)容。
[Abstract]:People often say, "the eyes are the windows of the soul." For congenital or acquired reasons, thousands of people can not see the world. The daily life of blind people is restricted by many limitations, such as the inability to detect danger in time when walking, which brings serious problems to the travel of blind people. With the rapid development of computer technology and communication technology and the rapid development of visual equipment for the blind, more and more researchers devote themselves to the research of related technology. In this paper, two aspects of dynamic target detection and static object edge detection are studied. The following works are accomplished: firstly, various traditional algorithms and applicable scenes are analyzed, and an improved algorithm suitable for blind walking assistance is adopted. In the aspect of dynamic target detection, ViBe algorithm is used to update the background and count to reinitialize the background model, and the adaptive threshold method is used to extract the edge of the static target. Then the improved algorithm and the traditional algorithm are simulated by MATLAB. The comparison of F_Measure parameters and subjective observation shows that, The recall rate of the improved dynamic target detection algorithm is 10% higher than that of the original algorithm, and the accuracy of the improved algorithm is 6% higher than that of the original algorithm. The improved static target edge detection algorithm can effectively extract interested edge information and eliminate invalid interference. Then the improved algorithm is implemented by Verilog hardware circuit, and the hardware circuit is simulated and analyzed by ModelSim. Finally, the target detection system is set up, which is configured from camera to VGA display, and the processing effect of the whole system is verified on the development board. The result of hardware implementation is compared with the result of MATLAB processing. The maximum relative error between the result of hardware processing and the result of software processing is 4. 3, hardware implementation to meet the design requirements. The experimental results of target detection show that dynamic target detection combined with ViBe algorithm and counting updating background model and counting reinitializing background model strategy can be more suitable for moving scene target detection. The adaptive threshold can reduce the interference of irrelevant information in static target edge detection. The target detection is realized by hardware circuit, which meets the real-time requirement better and enriches the research content of image processing in visual prosthesis.
【學(xué)位授予單位】：西安理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN791;TP391.41

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