SKEWED SYMMETRY DETECTION OF QUADRIC SURFACE SOLIDS UNDER ORTHOGRAPHIC PROJECTION

The skewed symmetry detection plays an improtant role in three-dimensional（3-D） reconstruction. The skewed symmetry depicts a real symmetry viewed from some unknown viewing directions. And the skewed symmetry detection can decrease the geometric constrains and the complexity of 3-D reconstruction. The detection technique for the quadric curve ellipse proposed by Sugimoto is improved to further cover quadric curves including hyperbola and parabola. With the parametric detection, the 3-D quadric curve projection matching is automatical- ly accomplished. Finally, the skewed symmetry surface of the quadric surface solid is obtained. Several examples are used to verify the feasibility of the algorithm and satisfying results can be obtained.

A Method of Image Symmetry Detection Based on Phase Information

Traditional methods for detecting symmetry in image suffer greatly from the contrast of image and noise, and they all require some preprocessing. This paper presents a new method of image symmetry detection. This method detects symmetry with phase information utilizing IogGabor wavelets,because phase information is stable and significant, while symmetric points produce patterns easy to be recognised and confirmable in local phase. Phase method does not require any preprocessing, and its result is accurate or invariant to contrast, rotation and illumination conditions. This method can detect mirror symmetry, rotating symmetry and curve symmetry at one time. Results of experiment show that, compared with pivotal element algorithm based on intensity information, phase method is more accurate and robust.

Symmetry detection of rotating patterns based on rotational Doppler effect of light

We propose a method for detecting the symmetry of rotating patterns based on the rotational Doppler effect(RDE)of light.The basic mechanisms of the RDE are introduced,and the spiral harmonic distribution of rotating patterns is analyzed.By irradiating the rotating pattern using a superimposed optical vortex and analyzing the amplitude of the RDE signal,the spiral harmonic distribution of the pattern can be measured,and then its symmetry can be detected.We demonstrate this method experimentally by using patterns with different symmetries and shapes.As the method does not need to receive the scattered light completely and accurately,it promises potential application in detecting symmetrical rotating objects at a long distance.

In-pit coal mine personnel uniqueness detection technology based on personnel positioning and face recognition

Since the coal mine in-pit personnel positioning system neither can effectively achieve the function to detect the uniqueness of in-pit coal-mine personnel nor can identify and eliminate violations in attendance management such as multiple cards for one person, and swiping one's cards by others in China at present. Therefore, the research introduces a uniqueness detection system and method for in-pit coal-mine personnel integrated into the in-pit coal mine personnel positioning system, establishing a system mode based on face recognition + recognition of personnel positioning card + release by automatic detection. Aiming at the facts that the in-pit personnel are wearing helmets and faces are prone to be stained during the face recognition, the study proposes the ideas that pre-process face images using the 2D-wavelet-transformation-based Mallat algorithm and extracts three face features: miner light, eyes and mouths, using the generalized symmetry transformation-based algorithm. This research carried out test with 40 clean face images with no helmets and 40 lightly-stained face images, and then compared with results with the one using the face feature extraction method based on grey-scale transformation and edge detection. The results show that the method described in the paper can detect accurately face features in the above-mentioned two cases, and the accuracy to detect face features is 97.5% in the case of wearing helmets and lightly-stained faces.

Roof model recommendation for complex buildings based on combination rules and symmetry features in footprints

Currently,very few roof shape information for complex buildings is available on OSM.Moreover,additional data requirements(e.g.3D point clouds)limit the applicability of many roof reconstruction approaches.To mitigate this issue,we propose an approach to roof shape recommendations for complex buildings by exploring the inherited characteristics of building footprints:the disclosure of rectangles combinations in a partition of footprints and the symmetrical features of footprints.First,it decomposes a complex footprint into rectangles by using an advanced minimal non-overlapping cover algorithm.Second,a graph-based symmetry detection algorithm is proposed to identify all the symmetrical sub-clusters in partitions.Then,a set of selection rules are defined to rank partitions,and the best ones are chosen for roof shape recommendation.Finally,a set of combination rules and a symmetry rule are defined.It enables to evaluate the probability of a footprint being a certain combination of roof shapes.Experimental results show the growth of the probability of correctly recommending roof shapes for single rectangles and buildings from a prior probability of 17–45%and from a prior probability of 0.29–14.3%,removing 60%and 93%of the incorrect roof shape options,respectively.