Surface reconstruction of complex contour lines based on chain code matching technique

A new method for solving the tiling problem of surface reconstruction is proposed. The proposed method uses a snake algorithm to segment the original images, the contours are then transformed into strings by Freeman＇ s code. Symbolic string matching technique is applied to establish a correspondence between the two consecutive contours. The surface is composed of the pieces reconstructed from the correspondence points. Experimental results show that the proposed method exhibits a good behavior for the quality of surface reconstruction and its time complexity is proportional to mn where m and n are the numbers of vertices of the two consecutive slices, respectively.

Multiple fault diagnosis of down-hole conditions of sucker-rod pumping wells based on Freeman chain code and DCA

It is important to achieve continuous, stable and efficient pumping well operation in actual oilfield operation. Down-hole pumping well working conditions can be monitored in real-time and a reasonable production scheme can be designed when computer diagnosis is used. However, it is difficult to make a comprehensive analysis to supply efficient technical guidance for operation of the pumping well with multiple faults of down-hole conditions, which cannot be effectively dealt with by the common methods. To solve this problem, a method based on designated component analysis （DCA） is used in this paper. Freeman chain code is used to represent the down-hole dynamometer card whose important characteristics are extracted to construct a designated mode set. A control chart is used as a basis for fault detection. The upper and lower control lines on the control chart are determined from standard samples in normal working conditions. In an incompletely orthogonal mode, the designated mode set could be divided into some subsets in which the modes are completely orthogonal. The observed data is projected into each designated mode to realize fault detection according to the upper and lower control lines. The examples show that the proposed method can effectively diagnose multiple faults of down-hole conditions.

SAR IMAGE RECOGNITION BASED ON MULTI-ASPECT OF SHADOW INFORMATION

The traditional synthetic aperture radar（SAR） image recognition techniques focus on the electro magnetic （EM） scattering centers, ignoring the important role of the shadow information on the SAR image recognition. It is difficult to classify targets by the shadow information independently, because the shadow shape is dependent on the radar aspect angle, the depression angle and the resolution. Moreover, the shadow shapes of different targets are similar. When the multiple SAR images of one target from different aspects are available, the performance of the target recognition can be improved. Aimed at the problem, a multi-aspect SAR image recognition technique based on the shadow information is developed. It extracts shadow profiles from SAR images, and takes chain codes as the feature vectors of targets. Then, feature vectors on multiple aspects of the same target are combined with feature sequences, and the hidden Markov model （HMM） is applied to the feature sequences for the target recognition. The simulation result shows the effectiveness of the method.

A novel method for eliminating rotation deviation in sequential images mosaic

To eliminate rotation deviation of sequential images mosaic when measuring linear dimensions of large scale parts with computer vision, a novel algorithm based on the chain code searching method is proposed. After image preprocessing, including image filtering, image segmentation, and edge detection, the chain code length of the contour line can be searched out by the proposed method. Then, the angle from the contour line to the coordinate axis is computed with the length of the contour line. After that, the sequence is rotated in the opposite direction and the rotation deviation is eliminated. It is prepared for the next mosaic of sequences in eliminating shifting deviation. Experiments are carried out on parts with a linear profile rotating angle from 0° to 9°. The results show that compared with the commonly used Hough transform, the new method has higher precision and faster speed, which is important in realizing online high precision measurements of large scale parts with a linear profile.

Three dimensional particles identification and shape parameters research on coarse aggregates of asphalt mixture using X-ray CT images

In this paper a series of digital image processing methods were adopted for getting separated coarse aggregates from asphalt mixture specimen using high-resolution X-ray Computed Tomography (CT) images.The existing three dimensional (3D) particles matching methods based on two dimensional (2D) continuous cross-sections were analyzed and a new 'overlap area method' was presented.After the 3D particles were extracted one by one successfully,the basic parameters of each aggregate:perimeter,area,surface area,and volume were calculated by chain code method.Finally,the 3D mass center coordinates and the sphericity index were introduced.

A man-made object detection algorithm based on contour complexity evaluation

Man-made object detection is of great significance in both military and civil areas, such as search-and-rescue missions at sea, traffic signs recognition during visual navigation, and targets location in a military strike. Contours of man-made objects usually consist of straight lines, corner points, and simple curves. Motivated by this observation, a man-made object detection method is proposed based on complexity evaluation of object contours. After salient contours which keep the crucial information of objects are accurately extracted using an improved mean-shift clustering algorithm, a novel approach is presented to evaluate the complexity of contours. By comparing the entropy values of contours before/after sampling and linear interpolation, it is easy to distinguish between man-made objects and natural ones according to the complexity of their contours.Experimental results show that the presented method can effectively detect man-made objects when compared to the existing ones.