Papers by Keyword: Shape Recognition

Abstract: Shape is the inherence characteristic of an object in the image, and it is the important character used for the object recognition. So it is significant for object recognition based on shape. This paper presents a contour-based method of feature extraction and shape recognition. First the object contour is translated into a 1-D contour curve. Secondly the curve is smoothed to restrain the noise. The number of peaks of the curve is achieved as well as the areas which contained between adjacent peak-valley, then the latter is followed by Discrete Fourier Transformation (DFT). Then two kinds of features ate extracted which are invariant to translation, scaling and rotation transformations. By using the features, a two-stake recursive algorithm for recognition is proposed. Experimental results show that this method is simple and efficient.

Abstract: Development of integrated database including casting shapes with their casting design, technical knowledge, and thermophysical properties of the casting alloys were introduced in the present study. For the shape database, a number of casting products are scanned by using by using industrial computer tomography and compiled to the shape database. Each shape data in the database has also parametric 3D modeling data, not only the product but also its casting design. If casting engineer want to design new casting, similar casting shape with casting design can be easily retrieved from the shape database, and easily modified and adapted to the new casting. Technical knowledge of the various casting processes and their manufacturing process of the castings were compiled and the search engine for the knowledge was developed. Database of thermophysical properties of the casting alloys were obtained by the experimental study or calculation based on CALPHAD approach, and the properties were used for the in-house computer simulation of casting process. The databases were linked with intelligent casting expert system developed in e-design center, KITECH. It is expected that the databases can help non casting experts to devise the casting and its process. Various examples of the application by using the databases were shown in the present study.

Abstract: Shape recognition methods based on one-dimensional global feature Fourier descriptors have been widely used for the computational simplicity and high recognition rate. However, in cases of occlusion, local deformation or other complex degradation this approach shows poor performance. In this paper we present a new shape recognition method with a novel shape similarity metric, which fuses three different metrics, all of which are rotation, translation and scaling invariant. These metrics takes into account the normalized shape variance, phase correlation and modified Fourier descriptor. Experimental results show that the proposed method has high recognition rate even when the object undergoes some shape deformation. When compared with other traditional shape recognition methods, the proposed method demonstrates significantly improved performance.

Abstract: This paper covers brain tumor diagnosis system based on image analysis and mining and its application. The system use the algorithm of fuzzy region competition, extracts shape feature factors to classify tumor shape, maps shape classification extracted automatically and other medical image features to numbers and then feed to bayesian network to sort the brain tumor automatically.

Abstract: Information extraction is an important part of the image processing. As the economic and technological development, the image quickly extracts information technology has been gained more needs and applications in many society fields. At home and abroad, there are many scholars to study how to quickly extract useful information from the image. Gray, binarization, the largest connected block extraction, contour extraction, corrosion, expansion and circle fitting technique have been used in this paper to match a known circle from a large number of irregular rounds.

Abstract: This paper presents the general structure, implementation features and a software module for tracing, visualization, shape recognition, measurement and efficiency evaluation for 3D model generation of objects to grip by an anthropomorphic gripper. Viewing is possible with an advanced video camera and shape recognition is possible through classifiers method. After setting the object shape, the gripper will approach the target, and its displacement is measured. Implementation, and how to work with the software designed are possible in several steps that are specified and described. The performance evaluation of the software system is based on a series of external factors, the most important being: light conditions; quality of video device; capture size; the human factor through a series of experiments focused on the system's ability to cope with external factors above mentioned.

Abstract: The aim of this paper is robot with vision system to interact with its environment. The task considered is recognizing and finding objects extracted from the image space. The work presents a Matlab program for different objects colour and shape recognition. The image taken by a low cost Web camera is processed and information is transferred to a robot controller for moving above the identified object.

Abstract: Fractal geometry is an useful approach in pattern recognition. Many fractal recognition methods use global analysis of the shape. In this paper we present a new fractal recognition method based on a dependence graph obtained from the PIFS. Moreover, this method uses local analysis of the shape which improves the recognition rate. The recognition algorithms have been tested to provide a feasible classification of the possible errors present in our similar object images datebase.

Abstract: According to the qualitative characterization of the morphological features of the wear debris, Feature vector mathematics model of wear debris are built,which are based on Foruier parameter refining methord.Then the advantages of fuzzy system and neural network are taken to establish a kind of improved fuzzy neural network (IFNN) models and algorithm.which is used to realize the automatic classification and recognition of wear debris. An improved learning algorithm with the modified fuzzy weight is proposed on the basis of the fuzzy neurons model for the max-min fuzzy operator. The amount of calculation for the improved FNN model is reduced greatly and the convergence velocity is improved. At last ,the experiment results show that the recognition method based on the IFNN is good at algorithm convergence speed and recognition accuracy.

Abstract: In this paper, a shape recognition method based on Freeman chain code has been proposed. According to the detected corners, feature vector of a contour shape can be obtained. And the descriptor of each corner in the feature vector has three components, which are the normalized distance between the corner and the centroid of all the corners, the local main trend of both sides of the corners. By using the feature vector, the matching judgment has been given, and the results of the experiment are shown.