【摘要】：提出了一種基于近鄰主特征匹配的亞像素級(jí)位移測(cè)量方法.改進(jìn)后的近鄰主特征提取過(guò)程通過(guò)修正散度矩陣的構(gòu)造,最大化相鄰位移圖像塊投影距離,提高了算法的精度和穩(wěn)定性.通過(guò)將訓(xùn)練過(guò)程離線化,提出了基于近鄰主特征匹配的微納米位移測(cè)量算法,并通過(guò)仿真實(shí)驗(yàn)驗(yàn)證了圖像塊在不同大小和位置情況下算法的精度.在高精度納米平臺(tái)、高倍顯微鏡及標(biāo)準(zhǔn)柵格構(gòu)成的系統(tǒng)中進(jìn)行了多角度的實(shí)驗(yàn),驗(yàn)證了算法的有效性.算法的測(cè)量精度比傳統(tǒng)的圖像塊匹配方法提高了近10倍,特別是算法對(duì)于圖像塊位置和大小的選擇魯棒性更高.
[Abstract]:A subpixel level displacement measurement method based on nearest neighbor principal feature matching is proposed. By modifying the construction of divergence matrix, the improved nearest neighbor main feature extraction process maximizes the projection distance of adjacent displacement image blocks, and improves the accuracy and stability of the algorithm. By de-linearizing the training process, a micro-nanometer displacement measurement algorithm based on nearest neighbor principal feature matching is proposed, and the accuracy of the algorithm is verified by simulation experiments. Experiments on high precision nanoplatform, high power microscope and standard grid system are carried out to verify the effectiveness of the algorithm. The measurement accuracy of the algorithm is nearly 10 times higher than that of the traditional image block matching method, especially the robustness of the algorithm to the selection of the location and size of the image block.
【作者單位】： 東北大學(xué)計(jì)算機(jī)科學(xué)與工程學(xué)院;常熟理工學(xué)院計(jì)算機(jī)科學(xué)與工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(61305025) 江蘇省高校自然科學(xué)基金資助項(xiàng)目(15KJB520001) 中央高�；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)資金資助項(xiàng)目(N120404008)
【分類號(hào)】：TP391.41

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