Skeleton Information Research Articles

가상 모델을 이용한 움직임 추출 알고리즘

In this paper, we propose the movement detection algorithm by using virtual skeleton model. To do this, first, we eliminate error values by using conventioanl method based on RGB color model and eliminate unnecessary values by using the HSI color model. Second, we construct the virtual skeleton model with skeleton information of 10 peoples. After matching this virtual model to original image, we extract the real head silhouette by using the proposed circle searching method. Third, we extract the object by using the mean-shift algorithm and this head information. Finally, we validate the applicability of the proposed method through the various experiments in a complex environments.

Experiment and simulation study on construction of a three-dimensional network model

The construction of a network model is one of the key techniques in organic combination of microscopic flow experiment and simulation. The construction method of a three-dimensional network model is presented on the basis of CT scanning images in this paper. A series of CT slice images describing microscopic pore structure and fluid distribution of actual rock is obtained with the help of the industrial microfocus CT system. Based on the extraction of pore space skeleton, pore and throat information, the corresponding network model is established, and the conversion from three-dimensional CT image information to pore-throat size distribution and topological information is also achieved. The feature of this method lies in the fact that complicated pore space of rock may be characterized by pores and throats with a simple shape while keeping the geometry and flow characteristics. It is indicated that the calculated results of porosity, permeability, relative permeability curve and microscopic remaining oil distribution match very well the experimental results of water flooding and polymer flooding. This network model may fairly well characterize the rock microscopic pore-throat size and topological characteristics.

A fast, memory-efficient and parallelizable arc/circle segmentation algorithm

This paper presents a fast parallelizable arc/circle segmentation method with small memory cost. Firstly the proposed method extracts the edge and skeleton information in image space, records every line fragment in a multi-fork tree as a node which can be processed concurrently. For simplifying the computation, every line fragment is approximated by its piecewise linear polygon (PLG). After that local discrete curvature of each dominant point (DP) on the PLG is calculated and used to estimate the local arc’s existence approximately, the arc’s parameters are calculated simultaneously. Finally the inveracious arcs would be erased according to the results of arc verification and the arc fragments would be jointed by the arc combination and tracking. This proposed method can deal with the edge rupture, intersection and overlapping conditions. Furthermore it requires small memory space and the parallel processing technology can be implemented to make it faster.

The potential applications of cone beam computed tomography in the management of endodontic problems

To provide core information on cone beam computed tomography (CBCT) technology and its potential applications in endodontic practice. CBCT has been specifically designed to produce undistorted three-dimensional information of the maxillofacial skeleton as well as three-dimensional images of the teeth and their surrounding tissues. This is usually achieved with a substantially lower effective dose compared with conventional medical computed tomography (CT). Periapical disease may be detected sooner using CBCT compared with periapical views, and the true size, extent, nature and position of periapical and resorptive lesions can be assessed. Root fractures, root canal anatomy and the true nature of the alveolar bone topography around teeth may be assessed. CBCT scans are desirable to assess posterior teeth prior to periapical surgery, as the thickness of the cortical and cancellous bone can be accurately determined as can the inclination of roots in relation to the surrounding jaw. The relationship of anatomical structures such as the maxillary sinus and inferior dental nerve to the root apices may also be clearly visualized. CBCT has a low effective dose in the same order of magnitude as conventional dental radiographs. CBCT has numerous potential applications in the management of endodontic problems.

Shape representation based on mathematical morphology

This paper presents a novel shape representation algorithm based on mathematical morphology. It consists of two steps. Firstly, an input shape is decomposed into a union of meaningful convex subparts by a recursive scheme. Each subpart is obtained by repeatedly applying condition expansion to a seed, which is selected by utilizing the skeleton information. Secondly, the shape of each subpart is approximated by a morphological dilation of basic structuring elements. The location and direction of the subpart are represented respectively by two parameters. Thus the given shape is represented by a union set of a number of three-dimensional vectors. Experiments show that the new algorithm is immune to noise and occlusion, and invariant under rotation, translation and scaling. Compared to other algorithms, it achieves more natural looking shape components and more concise representation at lower computation costs and coding costs.

Mending broken handwriting with a macrostructure analysis method to improve recognition

Broken characters always create problems in handwriting recognition systems, especially those using boundary and/or skeleton information. This paper presents a macrostructure analysis (MSA) mending method based on skeleton and boundary information and an MSA that investigates the stroke tending direction and other properties of handwritings. A new skeleton end extension algorithm is introduced, which compensates the defectiveness of the skeletonization algorithm and obtains a satisfactory skeleton. When combined with suitable parameters, improved performance from a handwriting classifier is achieved. The experimental results from over 13 000 numerals show the efficiency and robustness of the proposed method, raising recognition rates by over 10% for broken handwritten digits, from 74.8% to 86.4%.

Asphalt Study by Neuronal Networks. Correlation between Chemical and Rheological Properties

In this paper we investigate the prediction of rheological properties of bitumens using some structural parameters calculated from 13 C NMR data. This study was carried out using methods of quantitative structure properties relationships (QSPR) and more particularly neural networks (NN). Such a mathematical tool can find out non linear relations between descriptors and properties. Two asphalt rheological properties, m (creep slope at low temperature) and G * /sin δ (stiffness at high temperature) were selected, whereas the descriptors are the average molecular parameters which characterize the hydrocarbon skeleton of bitumens. This work permitted to prove that the skeleton information contained in the average molecular parameters could be correlated to the m value but not to the G * /sin δ. Thus, the low-temperature rheological behavior appears to be highly dependent on the aliphatic part of the bitumens.

Morphological skeleton representation and coding of binary images

This paper presents the results of a study on the use of morphological set operations to represent and encode a discrete binary image by parts of its skeleton, a thinned version of the image containing complete information about its shape and size. Using morphological erosions and openings, a finite image can be uniquely decomposed into a finite number of skeleton subsets and then the image can be exactly reconstructed by dilating the skeleton subsets. The morphological skeleton is shown to unify many previous approaches to skeletonization, and some of its theoretical properties are investigated. Fast algorithms that reduce the original quadratic complexity to linear are developed for skeleton decomposition and reconstruction. Partial reconstructions of the image are quantified through the omission of subsets of skeleton points. The concepts of a globally and locally minimal skeleton are introduced and fast algorithms are developed for obtaining minimal skeletons. For images containing blobs and large areas, the skeleton subsets are much thinner than the original image. Therefore, encoding of the skeleton information results in lower information rates than optimum block-Huffman or optimum runlength-Huffman coding of the original image. The highest level of image compression was obtained by using Elias coding of the skeleton.