2012 International Conference on Frontiers in Handwriting Recognition, 2012
ABSTRACT We present a statistical hypothesis testing method for handwritten word segmentation alg... more ABSTRACT We present a statistical hypothesis testing method for handwritten word segmentation algorithms. Our proposed method can be used along with any word segmentation algorithm in order to detect over-segmented or under-segmented errors or to adapt the word segmentation algorithm to new data in an unsupervised manner. The main idea behind the proposed approach is to learn the geometrical distribution of words within a sentence using a Markov chain or a Hidden Markov Model (HMM). In the former, we assume all the necessary information is observable, where in the latter, we assume the minimum observable variables are the bounding boxes of the words, and the hidden variables are the part of speech information. Our experimental results on a benchmark database show that not only we can achieve a lower over-segmentation and under-segmentation error rate, but also a higher correct segmentation rate as a result of the proposed hypothesis testing.
International Journal of Pattern Recognition and Artificial Intelligence, 1996
abstract Neural net is capable to recognize handwritten characters and the keg of is the extracti... more abstract Neural net is capable to recognize handwritten characters and the keg of is the extraction of features if the pattern feature do not include enough information of feature recognition objects or cannot extract the structure information reflecting the object feature, they can not be recognized therefore, the rapid and effective extraction of the features which reflect the structure information of objects is the key of pattern recognition due to joining script and separate script, handwritten characters are the problem of segmentation. ...
ABSTRACT Numeric strings such as identification numbers carry vital pieces of information in docu... more ABSTRACT Numeric strings such as identification numbers carry vital pieces of information in documents. In this paper, we present a novel algorithm for automatic extraction of numeric strings in unconstrained handwritten document images. The algorithm has two main phases: pruning and verification. In the pruning phase, the algorithm first performs a new segment-merge procedure on each text line, and then using a new regularity measure, it prunes all sequences of characters that are unlikely to be numeric strings. The segment-merge procedure is composed of two modules: a new explicit character segmentation algorithm which is based on analysis of skeletal graphs and a merging algorithm which is based on graph partitioning. All the candidate sequences that pass the pruning phase are sent to a recognition-based verification phase for the final decision. The recognition is based on a coarse-to-fine approach using probabilistic RBF networks. We developed our algorithm for the processing of real-world documents where letters and digits may be connected or broken in a document. The effectiveness of the proposed approach is shown by extensive experiments done on a real-world database of 607 documents which contains handwritten, machine-printed and mixed documents with different types of layouts and levels of noise.
2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008
Image segmentation is an important step in medical image analysis. The Mumford-Shah (MS) model is... more Image segmentation is an important step in medical image analysis. The Mumford-Shah (MS) model is a powerful and robust segmentation technique. However, the numerical method of solving the MS model is difficult to implement. Although some alternative approaches have been presented, these methods are either inefficient or applicable only to some special cases. We present a new image segmentation model,
2010 11th International Conference on Control Automation Robotics & Vision, 2010
Abstract This paper presents an advanced age-determination technique that combines holistic and ... more Abstract This paper presents an advanced age-determination technique that combines holistic and local features derived from an image of the face. A 30×1 Active Appearance Model (AAM) linear encoding of each face is produced to work as holistic features. Meanwhile, ...
2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems, 2009
AbstractIn this paper, we introduce a novel age estimation technique that combines Active Appear... more AbstractIn this paper, we introduce a novel age estimation technique that combines Active Appearance Models (AAMs) and Support Vector Machines (SVMs), to dramatically improve the accuracy of age estimation over the current state-of-the-art techniques. In this method, ...
Sensor Fusion IV: Control Paradigms and Data Structures, 1992
A method for reconstruction of 3D object models from multiple views of range image is proposed. I... more A method for reconstruction of 3D object models from multiple views of range image is proposed. It is very important to use these partially redundant data effectively to get an integrated, complete and accurate object model. The object shape is unconstrained, curved surfaces are allowed. From each view of range image, surfaces are segmented and fitted into planar and quadratic patches by a robust residual analysis method (we address this method in another paper). Analyzing the errors of fitted surfaces from each view, the final expressions of the surfaces are merged from every view. A boundary representative model (B-rep) is used to express the final complete object. The method can be used to create 3D models for object recognition.
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, 2010
In this paper, we introduce an advanced age determination technique that combines a feature set d... more In this paper, we introduce an advanced age determination technique that combines a feature set derived from an image of the face using multi-factored Principal Components Analysis (PCA) on the shape of the face and its features and the skin of the face to produce a 30×1 ...
2012 International Conference on Frontiers in Handwriting Recognition, 2012
ABSTRACT We present a statistical hypothesis testing method for handwritten word segmentation alg... more ABSTRACT We present a statistical hypothesis testing method for handwritten word segmentation algorithms. Our proposed method can be used along with any word segmentation algorithm in order to detect over-segmented or under-segmented errors or to adapt the word segmentation algorithm to new data in an unsupervised manner. The main idea behind the proposed approach is to learn the geometrical distribution of words within a sentence using a Markov chain or a Hidden Markov Model (HMM). In the former, we assume all the necessary information is observable, where in the latter, we assume the minimum observable variables are the bounding boxes of the words, and the hidden variables are the part of speech information. Our experimental results on a benchmark database show that not only we can achieve a lower over-segmentation and under-segmentation error rate, but also a higher correct segmentation rate as a result of the proposed hypothesis testing.
International Journal of Pattern Recognition and Artificial Intelligence, 1996
abstract Neural net is capable to recognize handwritten characters and the keg of is the extracti... more abstract Neural net is capable to recognize handwritten characters and the keg of is the extraction of features if the pattern feature do not include enough information of feature recognition objects or cannot extract the structure information reflecting the object feature, they can not be recognized therefore, the rapid and effective extraction of the features which reflect the structure information of objects is the key of pattern recognition due to joining script and separate script, handwritten characters are the problem of segmentation. ...
ABSTRACT Numeric strings such as identification numbers carry vital pieces of information in docu... more ABSTRACT Numeric strings such as identification numbers carry vital pieces of information in documents. In this paper, we present a novel algorithm for automatic extraction of numeric strings in unconstrained handwritten document images. The algorithm has two main phases: pruning and verification. In the pruning phase, the algorithm first performs a new segment-merge procedure on each text line, and then using a new regularity measure, it prunes all sequences of characters that are unlikely to be numeric strings. The segment-merge procedure is composed of two modules: a new explicit character segmentation algorithm which is based on analysis of skeletal graphs and a merging algorithm which is based on graph partitioning. All the candidate sequences that pass the pruning phase are sent to a recognition-based verification phase for the final decision. The recognition is based on a coarse-to-fine approach using probabilistic RBF networks. We developed our algorithm for the processing of real-world documents where letters and digits may be connected or broken in a document. The effectiveness of the proposed approach is shown by extensive experiments done on a real-world database of 607 documents which contains handwritten, machine-printed and mixed documents with different types of layouts and levels of noise.
2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008
Image segmentation is an important step in medical image analysis. The Mumford-Shah (MS) model is... more Image segmentation is an important step in medical image analysis. The Mumford-Shah (MS) model is a powerful and robust segmentation technique. However, the numerical method of solving the MS model is difficult to implement. Although some alternative approaches have been presented, these methods are either inefficient or applicable only to some special cases. We present a new image segmentation model,
2010 11th International Conference on Control Automation Robotics & Vision, 2010
Abstract This paper presents an advanced age-determination technique that combines holistic and ... more Abstract This paper presents an advanced age-determination technique that combines holistic and local features derived from an image of the face. A 30×1 Active Appearance Model (AAM) linear encoding of each face is produced to work as holistic features. Meanwhile, ...
2009 IEEE 3rd International Conference on Biometrics: Theory, Applications, and Systems, 2009
AbstractIn this paper, we introduce a novel age estimation technique that combines Active Appear... more AbstractIn this paper, we introduce a novel age estimation technique that combines Active Appearance Models (AAMs) and Support Vector Machines (SVMs), to dramatically improve the accuracy of age estimation over the current state-of-the-art techniques. In this method, ...
Sensor Fusion IV: Control Paradigms and Data Structures, 1992
A method for reconstruction of 3D object models from multiple views of range image is proposed. I... more A method for reconstruction of 3D object models from multiple views of range image is proposed. It is very important to use these partially redundant data effectively to get an integrated, complete and accurate object model. The object shape is unconstrained, curved surfaces are allowed. From each view of range image, surfaces are segmented and fitted into planar and quadratic patches by a robust residual analysis method (we address this method in another paper). Analyzing the errors of fitted surfaces from each view, the final expressions of the surfaces are merged from every view. A boundary representative model (B-rep) is used to express the final complete object. The method can be used to create 3D models for object recognition.
2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, 2010
In this paper, we introduce an advanced age determination technique that combines a feature set d... more In this paper, we introduce an advanced age determination technique that combines a feature set derived from an image of the face using multi-factored Principal Components Analysis (PCA) on the shape of the face and its features and the skin of the face to produce a 30×1 ...
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