imagerecognition in smart systems and internet of things applications is rapidly developing. Significant advances in mobile computing technology and machinelearning are expanding horizons to use imagerecognition in...
详细信息
images constitute data that live in a very high dimensional space, typically of the order of hundred thousand dimensions. Drawing inferences from correlated data of such high dimensions often becomes intractable. Ther...
详细信息
ISBN:
(纸本)3540305068
images constitute data that live in a very high dimensional space, typically of the order of hundred thousand dimensions. Drawing inferences from correlated data of such high dimensions often becomes intractable. Therefore traditionally several of these problems like face recognition, object recognition, scene understanding etc. have been approached using techniques in patternrecognition. Such methods in conjunction with methods for dimensionality reduction have been highly popular and successful in tackling several imageprocessing tasks. Of late, the advent of cheap, high quality video cameras has generated new interests in extending still image-based recognition methodologies to video sequences. The added temporal dimension in these videos makes problems like face and gait-based human recognition, event detection, activity recognition addressable. Our research has focussed on solving several of these problems through a patternrecognition approach. Of course, in video streams patterns refer to both patterns in the spatial structure of image intensities around interest points and temporal patterns that arise either due to camera motion or object motion. In this paper, we discuss the applications of patternrecognition in video to problems like face and gait-based human recognition, behavior classification, activity recognition and activity based person identification.
The proceedings contains 115 papers from the 4th internationalconference on computer science and informatics, JCIS '98 and the 1stinternational workshop on high performance computer vision, patternrecognition, ...
详细信息
The proceedings contains 115 papers from the 4th internationalconference on computer science and informatics, JCIS '98 and the 1stinternational workshop on high performance computer vision, patternrecognition, and imageprocessing, Volume 4. Topics discussed include: maintenance of controller software components using adaptation algorithms;construction methods of fuzzy decision trees;a comparison of wormhole routing algorithms in Cayley graphs;performance issues in multilevel secure database systems;visualizing distributed object systems;twisted cubes with fast optimal routing algorithms;multicommodity flow in networks;and a distributed connectivity algorithm for ad hoc networks.
In this paper our main focus is to discover different machinelearning techniques that are useful biometric System. As biometric authentication system is a combination of both imageprocessing and patternrecognition,...
详细信息
In this research work, local binary pattern (LBP)-based automatic target recognition system is proposed for classification of various categories of moving civilian targets using their infrared image signatures. Target...
详细信息
ISBN:
(纸本)9789811021046;9789811021039
In this research work, local binary pattern (LBP)-based automatic target recognition system is proposed for classification of various categories of moving civilian targets using their infrared image signatures. Target recognition in infrared images is demanding owing to large variations in target signature and limited target to background contrast. This demands robust features/descriptors which can represent possible variations of the target category with minimal intra class variance. LBP, a simple yet efficient texture operator initially proposed for texture recognition of late is gaining popularity in face and object recognition applications. In this work, the suitability of LBP and two of its variants, local ternary pattern (LTP), complete local binary pattern (CLBP) for the task of recognition in infrared images has been evaluated. The performance of the method is validated with target clips obtained from 'CSIR-CSIO moving object thermal infrared imagery dataset'. The number of classes is four-three different target classes (Ambassador, Auto and Pedestrian) and one class representing the background. Classification accuracies of 89.48 %, 100 % and 100 % were obtained for LBP, LTP and CLBP, respectively. The results indicate the suitability of LBP operator for target recognition in infrared images.
This paper presents a fractal analysis of bone X-ray images for automatic recognition of degree of osteoporosis and fracture risks. The weakly textured trabecular pattern in an image is enhanced by using the coherence...
详细信息
This paper presents a fractal analysis of bone X-ray images for automatic recognition of degree of osteoporosis and fracture risks. The weakly textured trabecular pattern in an image is enhanced by using the coherence map. A new method for 2-D power spectrum estimation with correction of modulation transfer function is introduced. The directional fractal dimensions computed from projection power spectra across various angles provide effective features for computer-assisted pattern classification of osteopororsis.
As the premise of feature extraction and patternrecognition, image segmentation is one of the fundamental approaches of digital imageprocessing. This paper enumerates and reviews main image segmentation algorithms, ...
详细信息
ISBN:
(纸本)9780769535579
As the premise of feature extraction and patternrecognition, image segmentation is one of the fundamental approaches of digital imageprocessing. This paper enumerates and reviews main image segmentation algorithms, then presents basic evaluation methods for them, finally discusses the prospect of image segmentation. Some valuable characteristics of image segmentation come out after a large number of comparative experiments.
An approach based on genetic algorithms was presented for learning fuzzy prototypical concept descriptions. The approach was implemented in a system called FuzzyProto, which handled only numeric attributes and produce...
详细信息
An approach based on genetic algorithms was presented for learning fuzzy prototypical concept descriptions. The approach was implemented in a system called FuzzyProto, which handled only numeric attributes and produced one prototype for each class. In this approach ideas developed in fuzzy set theory, cognitive science, genetic algorithms, and statistics were integrated. Preliminary experimental results demonstrated the potential of this approach of becoming an effective learning system for graded fuzzy concepts.
This paper provides an empirical study for feature learning based on induction. We encode image data into first-order expressions and compute their least generalization. An interesting question is whether the least ge...
详细信息
ISBN:
(数字)9783030974541
ISBN:
(纸本)9783030974541;9783030974534
This paper provides an empirical study for feature learning based on induction. We encode image data into first-order expressions and compute their least generalization. An interesting question is whether the least generalization can extract a common pattern of input data. We introduce three different methods for feature extraction based on symbolic manipulation. We perform experiments using the MNIst datasets and show that the proposed methods successfully capture features from training data and classify test data in around 90% accuracies. The results of this paper show potentials of induction and symbolic reasoning to feature learning or patternrecognition from raw data.
Dynamic gesture recognition in video stream has been studied extensively in recent years. To provide efficient and consistent of dynamic hand gesture recognition technique, Hierarchical Dynamic Vision Model (HDVM) whi...
详细信息
ISBN:
(纸本)9781424420957
Dynamic gesture recognition in video stream has been studied extensively in recent years. To provide efficient and consistent of dynamic hand gesture recognition technique, Hierarchical Dynamic Vision Model (HDVM) which based on dynamic Bayesian networks (DBNs) is proposed for automatically recognizing human hand gestures in this paper. HDVM consists of the fast differential color tracking algorithm (DCTA) for tracking object trajectory and the motion pattern analyzer (MPA) for recognizing the hand gestures. In this paper, the proposed model is able to recognize three dynamic hand gestures through the low-level image analysis. In the low-level imageprocessing, both motion trajectories and motion directions generated from hand part are used as features after segmentation.
暂无评论