Based on the characteristics of an original meteorological chart, Matlab software is used to design an algorithm that can independently extract some meteorological information from literature and analyze the data. Thr...Based on the characteristics of an original meteorological chart, Matlab software is used to design an algorithm that can independently extract some meteorological information from literature and analyze the data. Through the digitization of meteorological charts, it is easy to analyze and process meteorological chart data.展开更多
A graphic processing unit (GPU)-accelerated biological species recognition method using partially connected neural evolutionary network model is introduced in this paper. The partial connected neural evolutionary netw...A graphic processing unit (GPU)-accelerated biological species recognition method using partially connected neural evolutionary network model is introduced in this paper. The partial connected neural evolutionary network adopted in the paper can overcome the disadvantage of traditional neural network with small inputs. The whole image is considered as the input of the neural network, so the maximal features can be kept for recognition. To speed up the recognition process of the neural network, a fast implementation of the partially connected neural network was conducted on NVIDIA Tesla C1060 using the NVIDIA compute unified device architecture (CUDA) framework. Image sets of eight biological species were obtained to test the GPU implementation and counterpart serial CPU implementation, and experiment results showed GPU implementation works effectively on both recognition rate and speed, and gained 343 speedup over its counterpart CPU implementation. Comparing to feature-based recognition method on the same recognition task, the method also achieved an acceptable correct rate of 84.6% when testing on eight biological species.展开更多
The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recogni...The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into speech.This system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been realized.Following this study,an acceleration of the GCM algorithm(AGCM)is proposed.The AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original method.To assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech synthesis.Our text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.展开更多
This paper proposes a simple and discriminative framework, using graphical model and 3D geometry to understand the diversity of urban scenes with varying viewpoints. Our algorithm constructs a conditional random field...This paper proposes a simple and discriminative framework, using graphical model and 3D geometry to understand the diversity of urban scenes with varying viewpoints. Our algorithm constructs a conditional random field （CRF） network using over-segmented superpixels and learns the appearance model from different set of features for specific classes of our interest. Also, we introduce a training algorithm to learn a model for edge potential among these superpixel areas based on their feature difference. The proposed algorithm gives competitive and visually pleasing results for urban scene segmentation. We show the inference from our trained network improves the class labeling performance compared to the result when using the appearance model solely.展开更多
传统的手工建筑工程量统计方法不仅费时而且容易出错,利用计算机自动完成工程量统计工作则可以很好地解决这一问题.介绍了一个基于规则的建筑结构图自动识别系统（automatic interpretation of structuredrawings,简称AISD）.该系统以...传统的手工建筑工程量统计方法不仅费时而且容易出错,利用计算机自动完成工程量统计工作则可以很好地解决这一问题.介绍了一个基于规则的建筑结构图自动识别系统（automatic interpretation of structuredrawings,简称AISD）.该系统以矢量化后的电子图档为基础,通过总结建筑工程图结构特征及绘图规则,自动分析图中的各种图形元素、符号以及其关系,理解各种部件信息,并加以综合,以获取正确的建筑工程钢筋用量.通过对工程图的特征进行详细的研究,总结出一套基于规则的适应不同类型工程图的理解方法.试验结果表明,这种方法为建筑工程图的自动识别和理解提供了一个可取的解决途径.展开更多
文摘Based on the characteristics of an original meteorological chart, Matlab software is used to design an algorithm that can independently extract some meteorological information from literature and analyze the data. Through the digitization of meteorological charts, it is easy to analyze and process meteorological chart data.
基金National Natural Science Foundation of China (No. 60975084)Natural Science Foundation of Fujian Province,China (No.2011J05159)
文摘A graphic processing unit (GPU)-accelerated biological species recognition method using partially connected neural evolutionary network model is introduced in this paper. The partial connected neural evolutionary network adopted in the paper can overcome the disadvantage of traditional neural network with small inputs. The whole image is considered as the input of the neural network, so the maximal features can be kept for recognition. To speed up the recognition process of the neural network, a fast implementation of the partially connected neural network was conducted on NVIDIA Tesla C1060 using the NVIDIA compute unified device architecture (CUDA) framework. Image sets of eight biological species were obtained to test the GPU implementation and counterpart serial CPU implementation, and experiment results showed GPU implementation works effectively on both recognition rate and speed, and gained 343 speedup over its counterpart CPU implementation. Comparing to feature-based recognition method on the same recognition task, the method also achieved an acceptable correct rate of 84.6% when testing on eight biological species.
基金This work was funded by the Deanship of Scientific Research at Jouf University under Grant Number(DSR2022-RG-0114).
文摘The challenge faced by the visually impaired persons in their day-today lives is to interpret text from documents.In this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into speech.This system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been realized.Following this study,an acceleration of the GCM algorithm(AGCM)is proposed.The AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original method.To assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech synthesis.Our text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.
基金supported by the National Natural Science Foundation of China (60803103)Research Found For Doctoral Program of Higher Education of China (200800131026)Fundamental Research Funds for the Central Universities (2009RC0603, 2009RC0601)
文摘This paper proposes a simple and discriminative framework, using graphical model and 3D geometry to understand the diversity of urban scenes with varying viewpoints. Our algorithm constructs a conditional random field （CRF） network using over-segmented superpixels and learns the appearance model from different set of features for specific classes of our interest. Also, we introduce a training algorithm to learn a model for edge potential among these superpixel areas based on their feature difference. The proposed algorithm gives competitive and visually pleasing results for urban scene segmentation. We show the inference from our trained network improves the class labeling performance compared to the result when using the appearance model solely.
文摘传统的手工建筑工程量统计方法不仅费时而且容易出错,利用计算机自动完成工程量统计工作则可以很好地解决这一问题.介绍了一个基于规则的建筑结构图自动识别系统（automatic interpretation of structuredrawings,简称AISD）.该系统以矢量化后的电子图档为基础,通过总结建筑工程图结构特征及绘图规则,自动分析图中的各种图形元素、符号以及其关系,理解各种部件信息,并加以综合,以获取正确的建筑工程钢筋用量.通过对工程图的特征进行详细的研究,总结出一套基于规则的适应不同类型工程图的理解方法.试验结果表明,这种方法为建筑工程图的自动识别和理解提供了一个可取的解决途径.
