image covariance matrix 中文意思是什麼
image covariance matrix
解釋
圖像協方差矩陣- image : n 1 像，肖像，畫像；偶像。2 影像，圖像。3 相像的人（或物）；翻版。4 形像，典型。5 形像化的描繪。6...
- covariance : n. 【統計學】協方差，協變性；共離散。
- matrix : n （pl matrices 或matrixes）1 【解剖學】子宮；母體；發源地，策源地，搖籃；【生物學】襯質細胞；間...
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Firstly, to perform pca or lda on basis of such high - dimensional image vectors is a time - consuming process. secondly, the high dimensionality usually leads to singularity of the within - class covariance matrix, which is a trouble for calculation of fisher optimal discriminant vectors
這樣就從根本上避免了在高維的圖像向量空間內構造散布矩陣並計算特徵向量的困難，大幅度地降低了特徵抽取過程所耗費的計算量。 -
The conventional principal component analysis ( pca ) and fisher linear discriminant analysis ( lda ) are based on vectors. that is to say, if we use them to deal with the image recognition problem, the first step is to transform original image matrices into same dimensional vectors, and then rely on these vectors to evaluate the covariance matrix and to determine the projector
所提出的這兩種方法的共同特點是，在進行圖像特徵抽取時，不需要事先將圖像矩陣轉化為高維的圖像向量，而是直接利用圖像矩陣本身構造圖像散布矩陣，然後基於這些散布矩陣進行主分量分析與線性鑒別分析。 -
First we construct a covariance matrix from sample images, then compute the eigenvalues and corresponding eigenvectors of the covariance matrix, construct a feature matrix with the eigenvectors. then every images in database can be projected into the feature matrix and gain a projection vector, so does the input image. then we can judge the resemblance between input image with each image in database by computing the distance between their projection vectors
我們首先根據採集的樣本圖像構造一個協方差矩陣，然後求取該矩陣的特徵值，以這些矩陣特徵值對應的特徵向量構造出一個特徵空間，然後將輸入圖像向該特徵空間映射，將獲取的映射系數與樣本庫中圖像的映射系數進行距離計算，根據計算出的距離判定輸入圖像與樣本圖像間的匹配程度。 -
First we construct a covariance matrix from sample images, then compute the eigenvalues and corresponding eigenvectors of the covariance matrix, construct a feature matrix with the eigenvectors. then every image in database can be projected into the feature matrix and gain a projection vector, so does the input image. then we can judge the resemblance between input image with each image in database by computing the distance between their projection vectors
然後，根據採集的樣本圖像構造一個協方差矩陣，求取該矩陣的特徵值，以這些矩陣特徵值對應的特徵向量構造一個特徵空間，將輸入圖像向該特徵空間映射，計算獲取的映射系數與樣本庫中各類圖像的映射系數的歐基里德距離，根據計算出的距離判定輸入圖像與樣本圖像間的匹配程度。
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