Recently the multi-model recognition has been considered the development trend for the fast-developing biological recognition technology. Taking humanity cranio-maxillo-facial as the target, a novel recognition method...
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ISBN:
(纸本)9781424437702
Recently the multi-model recognition has been considered the development trend for the fast-developing biological recognition technology. Taking humanity cranio-maxillo-facial as the target, a novel recognition method is proposed in this paper. Starting from the mathematical model based on extracting characteristic parameters, the types of characteristic parameters is determined, and the features of different parameters are analyzed. Meanwhile the computational method of related parameters has been completed Finally, a new recognition algorithm based on these parameters is proposed and our preliminary simulation results indicate that this algorithm is effective.
this paper deals with plane extraction from a single moving camera through a new optical-flow cumulative process. We show how this c-velocity defined by analogy to the v-disparity in stereovision, could serve exhibiti...
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ISBN:
(纸本)9789896740009
this paper deals with plane extraction from a single moving camera through a new optical-flow cumulative process. We show how this c-velocity defined by analogy to the v-disparity in stereovision, could serve exhibiting any plane whatever their orientation. We focus on 3D-planar structures like obstacles, road or buildings. A translational camera motion being assumed, the c-velocity space is then a velocity cumulative frame in which planar surfaces are transformed into lines, straight or parabolic. We show in the paper how this representation makes plane extraction robust and efficient despite the poor quality of classical optical flow.
DNA microarrays are used in order to recognize the presence or absence of different biological components (targets) in a sample. therefore, the design of the microarrays which includes selecting short Oligonucleotide ...
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the proceedings contain 93 papers. the topics discussed include: the use of residuals in image denoising;edge-preserving image reconstruction with wavelet-domain edge continuation;hierarchical sampling with constraint...
ISBN:
(纸本)3642026109
the proceedings contain 93 papers. the topics discussed include: the use of residuals in image denoising;edge-preserving image reconstruction with wavelet-domain edge continuation;hierarchical sampling with constraints;image and video retargetting by darting;enhancement of the quality of images through complex mosaic configurations;multifocus image fusion using local phase coherence measurement;robust principal components for hyperspectral data analysis;cue integration for urban area extraction in remote sensing images;fuzzy Gaussian process classification model;an intensity and size invariant real time face recognition approach;learning structural models in multiple projection spaces;region classification for robust floor detection in indoor environments;suppression of foxing in historical books using inpainting;and enhancing the quality of color documents with back-to-front interference.
Numerical accuracy of moment invariants is very important for reliable feature extraction in biometric recognition and cryptosystems. this paper presents a novel approach to derive accuracy enhanced moment invariants ...
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ISBN:
(纸本)9783642026102
Numerical accuracy of moment invariants is very important for reliable feature extraction in biometric recognition and cryptosystems. this paper presents a novel approach to derive accuracy enhanced moment invariants that are invariant under translation, rotation, scaling, pixel interpolation and image cropping. the proposed approach defines a cosine based central moment and adopts a windowing mechanism to enhance accuracy of moment invariants under translation, rotation, scaling, pixel interpolation and image cropping. It derives moment invariants by extending the knowledge used in Hu's and Maitra's approaches. Simulation results show that the proposed moment invariants highly accurate than Hu's and Maitra's moment invariants.
Text mining refers to extract high-quality information including entities and relationships between them from text. Although several methods have been applied to extract protein interaction relationships and other inf...
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Video content processing and analysis is going through a transition from low-level feature based techniques to high-level semantics based approaches. In this paper, we describe Such a transition that low level feature...
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ISBN:
(纸本)9783642026102
Video content processing and analysis is going through a transition from low-level feature based techniques to high-level semantics based approaches. In this paper, we describe Such a transition that low level features are processed to extract four semantic patterns, leading to high-level content analysis for snooker videos. Such extracted semantics and recognised patterns include: (i) full court scenes for snooker match, (ii) close-tip view of snooker match;(iii) player's face, and (iv) audience's faces. Experimental results support that the proposed technique works well with snooker videos, providing a significant potential for automatic snooker video processing such its annotation, summarization and editing.
this paper introduces the Center for patternrecognition and Machine Intelligence (CENPARMI) Farsi dataset which can be used to measure the performance of handwritten recognition and word spotting systems. this datase...
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ISBN:
(纸本)9783642026102
this paper introduces the Center for patternrecognition and Machine Intelligence (CENPARMI) Farsi dataset which can be used to measure the performance of handwritten recognition and word spotting systems. this dataset is unique in terms of its large number of gray and binary images (432,357 each) consisting of dates, words, isolated letters, isolated digits, numeral strings, special symbols, and documents. the data was collected from 400 native Farsi writers. the selection of Farsi words has been based on their high frequency in financial documents. the dataset is divided into grouped and Ungrouped subsets which will give the user the flexibility of whether or not to use CENPARMI's pre-divided dataset (60% of the images are used as the Training set, 20% of the images as the Validation set, and the rest as the Testing set). Finally, experiments have been conducted on the Farsi isolated digits with a recognition rate of 96.85%.
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