In the process of large-scale chemical engineering, more useful industrial process information can be obtained by increasing measuring variables, defined as system features. However, the increase in amount of features will lead to the high computation cost and reduce the efficiency of the process monitoring system. To solve this issue, those features that are redundant or bring an incorrect result should be removed before the process monitoring. Feature selection is the issue of selecting a subset of most informative features from the full set of features. A novel multiple kernel learning based method is proposed for the feature selection. Distinguished with the literature, the feature selection problem is transformed into an optimization problem in the multiple kernel learning, which avoids the drawback called the “monotonic” problem in conventional feature selection methods. Finally, the performance of the proposed method for feature selection in process monitoring is demonstrated through the experiment in Tennessee Eastman benchmark process.

We study a pattern in the fingerprint called a crease, a kind of stripe which irregularly crosses the normal fingerprint patterns (ridges and valleys). Creases will cause spurious minutiae when using a conventional feature detection algorithm, and therefore decreases the recognition rate of fingerprint identification. By representing the crease using a parameterized rectangle, we design an optimal filter as a detector. We employ a multi-channel filtering framework to detect creases in different orientations. In each channel, PCA is used to extract a rectangle's parameters from the raw detected results. Our algorithm is demonstrated by experiments.

A robust framework is proposed for contour extraction and moving vehicle tracking. First, we establish a modified snake model and utilize directional information to guide the behavior of snaxels. Then, an adaptive shape restriction is embedded into the algorithm to govern the scope of the snake's motion. The spatio-temporal relationship between successive frames is estimated using a Kalman filter. These can improve the snake's robustness against noise or the presence of occlusion, which is inevitable in real tasks of traffic monitoring. Experimental results of the proposed framework on real traffic videos are satisfying and encouraging.

The palmprint has one special salient feature which is not salient in fingerprint. That is the crease. In a palmprint the creases are large in number and comparatively easy to extract. Creases are also approximately stable in a person's whole life, which qualifies them as features in palmprint recognition. We give creases an accurate definition which is fit for algorithm implementation. We devised a rather exquisite algorithm to extract all the creases in a palmprint whose success is mainly from a new different direction computing method and a thorough local analysis and a robust search algorithm. Based on the extracted creases, we devised a robust palmprint matching algorithm which is rotation and translation invariant. The crease extraction results and palmprint matching results show that the crease can be extracted successfully and crease-based palmprint matching is robust and accurate.

An algorithm for automatic cartridge identification using decision fusion based on Support Vector Machine (SVM) is proposed. First, several kinds of features are extracted by analyzing the marks of cartridges, and then they are integrated to make a final decision by using SVM. Experimental results illustrate the effectiveness of our algorithm.

This paper presents a novel stroke tracing approach to recovering the strokes from the handwriting images. It is carried out not only based on pixel by pixel, but considering the local relation of handwriting strokes. Firstly the primary skeletons of handwriting are produced through the binarization and thinning. Secondly, after the reliable skeletons and unreliable skeletons are classified based on the width information of handwriting, the strokes segments are obtained by the connecting and tracing on the reliable skeletons. Finally, for making the recovered strokes more natural, the post-processing of tracing is discussed. Experimental results show the effectiveness of the approach.