Many off-line handwritten word recognition systems have been proposed since the early nineties. Most systems reported high recognition rates, however, they overlooked a very important factor in the process;speed facto...
详细信息
In this paper we propose a handwritten numeral string recognition method composed of two HMM-based stages. the first stage uses an implicit segmentation strategy based on string contextual information to provide multi...
详细信息
We propose a word segmentation method for handwritten Korean text lines. It uses gap information to separate a text line into word units, where the gap is defined as a white-run obtained after a vertical projection of...
详细信息
this paper describes a graph grammar to modelize textured symbols in a graphics recognition framework. A textured symbol means a symbol consisting of repetitive structured patterns. We propose a method to infer a grap...
详细信息
ISBN:
(纸本)0769512631
this paper describes a graph grammar to modelize textured symbols in a graphics recognition framework. A textured symbol means a symbol consisting of repetitive structured patterns. We propose a method to infer a graph grammar front a structured texture detected in a document, anti the subsequent parser to decide whether a symbol is accepted by the grammar. the grammar is based on a Region Adjacency Graph representation of the vectorized document and the productions are based on the neighboring relations of the patterns forming the textured symbol. the syntactic framework is applied on an architectural plan understanding application.
A new direction in machine learning area has emerged from Vapnik's theory in support vectors machine and its applications on patternrecognition. In this paper, we propose a new SVM kernel family (KMOD) with disti...
详细信息
ISBN:
(纸本)0769512631
A new direction in machine learning area has emerged from Vapnik's theory in support vectors machine and its applications on patternrecognition. In this paper, we propose a new SVM kernel family (KMOD) with distinctive properties that allots, better discrimination in the feature space. the experiments that we carry out show its effectiveness on synthetic and large-scale data. We found KMOD behaving better than RBF and Exponential RBF kernels on the two-spiral problem. In addition, a digit recognition task was processed using the proposed kernel. the results show;at least, comparable performances to state of the art kernels.
this paper presents an original hybrid MLP-SVM method for unconstrained handwritten digits recognition. Specialized Support Vector Machines (SVMs) are introduced to improve significantly the MLP performances in local ...
详细信息
ISBN:
(纸本)0769512631
this paper presents an original hybrid MLP-SVM method for unconstrained handwritten digits recognition. Specialized Support Vector Machines (SVMs) are introduced to improve significantly the MLP performances in local areas around the separation surfaces between each pair of digit classes, in the input pattern space. this hybrid architecture is based on the idea that the correct digit class almost systematically belongs to the two maximum MLP outputs and that some pairs of digit classes constitute the majority of MLP substitutions (errors). Specialized local SVMs are introduced to detect the correct class among these mw classification hypotheses. the hybrid MLP-SVM recognizer achieves a recognition rate of 98.01%, for real mail zipcode digits recognition task, a performance better than several classifiers reported in recent researches.
this paper proposes a general local learning framework to effectively alleviate the complexities of classifier design by means of "divide and conquer" principle and ensemble method. the learning framework co...
详细信息
ISBN:
(纸本)0769512631
this paper proposes a general local learning framework to effectively alleviate the complexities of classifier design by means of "divide and conquer" principle and ensemble method. the learning framework consists of quantization layer and ensemble layer. After GLVQ and MLP are applied to the framework. the proposed method is tested on MNIST handwritten digit database. the obtained performance is very promising, an error rate with 0.99. which is comparable to that of LeNet5. one of the best classifiers on this database, Further, in contrast to LeNet7, our method is especially suitable for a large-scale real-world classification problem.
In a general situation. a document page may contain several script forms. For Optical Character recognition (OCR) of such a document page, it is necessary to separate the scripts before feeding them to their individua...
详细信息
ISBN:
(纸本)0769512631
In a general situation. a document page may contain several script forms. For Optical Character recognition (OCR) of such a document page, it is necessary to separate the scripts before feeding them to their individual OCR systems. In this paper, an automatic technique for the identification of printed Roman, Chinese, Arabic, Devnagari and Banglu text lines from a single document is proposed. Shape based features, statistical features and some features obtained from the concept of water reservoir. have been used for script identification. the proposed scheme has an accuracy of about 97.33%.
the problem of signature verification is in theory a patternrecognition task used to discriminate two classes, original and forgery signatures. Even after many efforts in order to develop new verification techniques ...
详细信息
ISBN:
(纸本)0769512631
the problem of signature verification is in theory a patternrecognition task used to discriminate two classes, original and forgery signatures. Even after many efforts in order to develop new verification techniques for static signature verification, the influence of the forgery types has not been extensively studied. this paper reports the contribution to signature verification considering different forgery types in an HMM framework. the experiments have shown that the error rates of the simple and random forgery signatures are very closed. this reflects the real applications in which the simple forgeries represent the principal fraudulent case. In addition, the experiments show promising results in skilled forgery verification by using simple static and pseudodinamic features.
Segmenting handwritten date fields on bank cheque images into three subimages corresponding to the Day, Month and Year is the first and critical step of our date recognition system. this paper describes a knowledge-ba...
详细信息
ISBN:
(纸本)0769512631
Segmenting handwritten date fields on bank cheque images into three subimages corresponding to the Day, Month and Year is the first and critical step of our date recognition system. this paper describes a knowledge-based segmentation system, which introduces different kinds of knowledge at different segmentation stages to improve the performance. the knowledge includes information on the writing style, syntactic and semantic constraints. etc. Results have shown that the system is very effective compared withthe previous structural feature based method.
暂无评论