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This paper proposes a novel method via dynamic tree to solve the non-rigid registration of point sets with large shape difference which is a difficult problem for existing methods. Affine ICP algorithm with bidirectional distance is employed to evaluate the similarity between two point sets, and then non-rigid registration is conducted on similar models and subjects. Subjects with accurate registration...
This article presents our recent study on fusion of information at feature and classifier output levels for improved performance of offline handwritten Devanagari word recognition. We consider here two state-of-the-art features, viz., Directional Distance Distribution (DDD) and Gradient-Structural-Concavity (GSC) features along with multi-class SVM classifiers. Here, we study various combinations...
In this paper, we propose an approach for two-dimensional shape representation and matching using the B-spline modelling and Dynamic Programming (DP), which is robust with respect to affine transformations such as translation, rotation, scale change and some distortions. Boundary shape is first splited into distinct parts based on the curvature. Curvature points are critical attributes for shape description,...
In this work, the merits of class-dependent image feature selection for real-world material classification is investigated. Current state-of-the-art approaches to material classification attempt to discriminate materials based on their surface properties by using a rich set of heterogeneous local features. The primary foundation of these approaches is the hypothesis that materials can be optimally...
3D Object recognition is one of the big problems in Computer Vision which has a direct impact in Robotics. There have been great advances in the last decade thanks to point cloud descriptors. These descriptors do very well at recognizing object instances in a wide variety of situations. Of great interest is also to know how descriptors perform in object classification tasks. With that idea in mind,...
We have studied the problem of retrieval of arbitrary object instances from a large point cloud data set. The context is autonomous robots operating for long periods of time, weeks up to months and regularly saving point cloud data. The ever growing collection of data is stored in a way that allows ranking candidate examples of any query object, given in the form of a single view point cloud, without...
This paper studies the computer-aided diagnosis technique potential in discriminating accurately benign masses among a given subset of 100 patients which makes it possible to degrade cases from Breast Imaging-Reporting and Data System (BIRADS) 3 to BIRADS 2 avoiding prospective biopsies. Such accuracy is required since expert radiologists assign BIRADS3 category by default mostly for reducing false...
A novel method for the detection and segmentation of nuclei and cells in Pap smear images is introduced. The method is based on a geometric analysis of iso- and edge-contours. For nuclei detection we employ isocontours taken at different levels of intensity and we report best detection (object) recall values as well as best segmentation precision values. For cell outline detection, we employ traditional...
Integrating legacy plant and process information into engineering, control, and enterprise systems may significantly increase the efficiency of managerial and technical operations in industrial facilities. The first step towards the pursued data integration is the extraction of relevant information from existing engineering documents, many of which are stored in vector-graphics-compatible formats...
This paper presents different approaches to extract information from large databases in order to process the gained information and find appropriate clusters. Starting from an unsorted collection of varying engineering parts in CAD format, the whole database will be automatically transformed to the non-proprietary IGES-format. Aided by Python-programmed macros controlling diverse measuring functions,...
In order to perform productive autonomous excavation of a fragmented rock pile, it is necessary to recognize the condition of the fragmented rock pile and to plan appropriate excavating motion according to the condition of the fragmented rock pile. In this paper, we propose imitation-based motion planning method, and develop a recognizer of rock pile condition and an excavating motion planner. We...
This work describes a photo-realistic generator that creates semi-automatically face images of unseen subjects. Unlike previously described methods for generating face imagery, the approach described herein incorporates texture and shape information in a single computational framework based on high dimensional encoding of variance and discriminant information from sample groups. The method produces...
In satellite communications, among all atmospheric effects, rain has the biggest impact on signal transmission, causing attenuation, polarization rotation and phase shift. Precise knowledge of statistical expectations for rain attenuation thus is of high practical relevance. Whereas often a unique relationship between rain rate and specific attenuation is used, it is well known that the variability...
Automatic fish recognition is a recent research work which is needed to assist marine scientists. Among most discriminative features, the fish outline is very efficient for fish recognition. In a previous work, we proposed a method for pattern recognition (classification and retrieval) based on signal registration and shape geodesics. In this paper, we introduce a preliminary step of pose estimation...
Research in traffic light recognition (TLR) has stagnated compared to related computer vision areas, such as pedestrian detection and and traffic sign recognition. We focus on the detection sub-problem, since this is the most challenging problem and solving this is the key to a successful TLR system. This is done by looking at four detectors from different author groups and their reported results...
There is thousands of organisms under the water and every group of organisms have many types or species. Some are dangerous and will attack when touched and some others will attack directly without any reason. In this research, a method that can recognize a stonefish, which is the most venomous fish in the world from a video to help divers or swimmers in open water to avoid danger, is presented. When...
In India like many other countries, the crimes especially against women are rising. One of the many reasons perhaps is the low conviction rate. The initial stage of criminal investigation starts with the exploration of evidences and eyewitnesses. An eyewitness can act as a guide to trace out the suspect. Her/his perception about the suspect can be useful to identify the criminal. Based on the descriptions...
The quality of the segmentation process directly affects the performance of the shape recognition. In this paper, we address the problem of shape recognition using only the available shape parts instead of the whole shape. For this purpose, we propose a shape parts recognition strategy that uses a robust distance based on geodesics in the shape space. The proposed combining strategy seeks to handle...
Electrocardiogram (ECG) is a key diagnostic tool to visualize the heart's activity and to study its normal or abnormal functioning. Physicians perform routine diagnosis by visually examining the shapes of ECG waveform. However, automatic processing and classification of ECG data would be extremely useful in patient monitoring and telemedicine systems. Such realtime applications require techniques...
While much work in the domain of traffic lights recognition is invested in the detection of traffic lights, classification of their exact state (including color phase and possible arrow pictogram) is often neglected. In this paper, we propose a robust approach for efficient video-based classification of said state with particular attention to the displayed pictogram and an additional ability to reject...
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