本文選題：生物散斑 + 三維成像��； 參考：《食品科學》2017年03期

【摘要】：三維成像技術(shù)能夠獲得樣品的空間信息,具有快速、方便、可實時的特點。為了縮短生物散斑技術(shù)的檢測時間,減小其應用的局限性,將三維成像技術(shù)引入到傳統(tǒng)生物散斑技術(shù)中,以期得到更好的預測效果。分別從兩個不同角度拍攝同一樣品的圖像信息,利用廣義差分法對圖像進行預處理,并運用灰度模板匹配法、小波變換法和對比度調(diào)制融合法對兩個角度的圖像進行匹配融合,以時間序列散斑圖灰度共生矩陣的參數(shù)對比度表示圖像的散斑活性,建立其對牛肉質(zhì)構(gòu)特性的預測模型。通過傳統(tǒng)相機標定法,獲得相機的內(nèi)外參數(shù),并利用相似三角形原理提取圖像的深度信息,對因物體擺放位置不同引起的誤差進行校正,使獲得的結(jié)果更加準確。結(jié)果表明,相似三角形原理可對樣品的深度信息進行校正。三維生物散斑技術(shù)能更好地對牛肉的硬度和咀嚼性進行預測,對3種圖像融合方法進行比較可知,小波變換法的預測效果最好,對硬度和咀嚼性的預測相關(guān)系數(shù)分別可達到0.944 4和0.928 8。
[Abstract]:Three-dimensional imaging technology can obtain spatial information of samples, which is fast, convenient and real-time. In order to shorten the detection time of biological speckle technology and reduce the limitation of its application, the 3D imaging technology is introduced into the traditional biological speckle technology in order to obtain better prediction effect. The image information of the same sample was taken from two different angles, the image was preprocessed by the generalized difference method, and the image from the two angles was matched and fused by gray template matching method, wavelet transform method and contrast modulation fusion method. The speckle activity of time series speckle pattern is represented by the contrast of the parameter of gray level co-occurrence matrix of time series speckle pattern, and the prediction model of beef texture property is established. Through the traditional camera calibration method, the internal and external parameters of the camera are obtained, and the depth information of the image is extracted by using the principle of similar triangle, and the error caused by the different position of the object is corrected, which makes the result more accurate. The results show that the similar triangle principle can correct the depth information of the sample. Three-dimensional biospeckle technique can better predict the hardness and chewiness of beef. The comparison of three image fusion methods shows that wavelet transform is the best method to predict beef hardness and chewiness. The predicted correlation coefficients for hardness and mastication were 0.944 4 and 0.928 8 respectively.
【作者單位】： 上海理工大學醫(yī)療器械與食品學院;
【基金】：“十二五”國家科技支撐計劃項目(2015BAK36B04) 國家自然科學基金面上項目(31271896) 上海市科委2015年長三角科技聯(lián)合攻關(guān)領(lǐng)域項目(15395810900)
【分類號】：TS251.52;TP391.41

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