The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The dynamometer card is a main method to analyze downhole working conditions of the beam pumping unit in actual operation. For computer based diagnosis mode, a method based on 16-directions chain codes and K-means clustering is proposed in this paper. First, the 16-directions chain codes are used to recreate boundary contour curve of the dynamometer card; then seven feature vectors which can accurately...
The impacts of facial makeup on automated face recognition system have received attention recently and studies have shown that facial cosmetics can compromise the accuracy of current face recognition techniques. Hence, there are groups of researchers endeavoring to develop the face recognition systems that are robust to facial makeup. In this work, the literatures on various techniques proposed to...
Discriminant Common Vectors (DCV) is proposed to solve small sample size problem. Face recognition encounters this dilemma where number of training samples is always smaller than the data dimension. In literature, it is shown that DCV is efficient in face recognition. In this paper, DCV is enhanced for further boosting its discriminating power. This modified version is namely Discriminative Discriminant...
Face spoofing attack is one of the recent security problems that face recognition systems are proven to be vulnerable to. The spoofing occurs when an attacker bypass the authentication scheme by presenting a copy of the face image for a valid user. Therefore, it's very easy to perform a face recognition spoofing attack with compare to other biometrics. This paper, presents a novel and efficient facial...
Face images always have significant intra-class variations due to different poses, illuminations and facial expressions. These variations trigger substantial deviation from the linearity assumption of data structure, which is essential in formulating linear dimension reduction technique. In this paper, we present a kernel based regularized graph embedding dimension reduction technique, known as kernel-based...
In this paper, we propose a novel method to determine whether a scanned text document is right side up or upside down. The text documents discussed here are limited to English, Chinese and Japanese where we find that the punctuation marks located on the bottom of the text line have a much more frequent occurrence than those on the top. Thus, by calculating the number of punctuation marks on the bottom...
Neighborhood Preserving Embedding (NPE) is an unsupervised linear dimensionality reduction technique which attempts to solve the ldquoout of samplerdquo problem in Locally Linear Embedding (LLE). This is done by introducing a linear transform matrix into LLE, and hence NPE can be perceived as a linear approximation to LLE. In this paper, we modify the original NPE for face recognition by embedding...
Face images are often very high-dimensional and complex. However, the actual underlying structure can be characterized by a small number of features. Hence, locally linear embedding (LLE) is proposed as a nonlinear dimension reduction technique to deal this problem. LLE learns the intrinsic manifold embedded in the high dimensional ambient space by minimizing the global reconstruction error of the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.