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In this paper we present a new method for writer identification, which extract original Local Binary Pattern(LBP) of different radius and Edge descriptors from the edge points of the handwriting. Then, we make combinations of these edge based features. Experimental results demonstrate that the combination of edge points based features outperform traditional features extracted from the whole text,...
Handwritten Characters Recognition has long been a tough problem in pattern recognition and machine learning. Some special tasks, such as automatic check preprocessing, require Handwritten Chinese Legal Amounts recognition as a prerequisite. Since we expect to utilize machine instead of human to process bank checks, the recognition rate in such task must reach a relatively high rate. This paper proposes...
Gabor features have been demonstrated to be very effective for face representation. Recently, non-sub sampled contour let transform (NSCT), which is a newly developed multi-resolution analysis tool based on contour let transform, is also used in facial image processing. In fact, the two image decomposition methods are performed from two different angles. To exploit complementarity of these features,...
A hidden Markov model (HMM) based method for Chinese legal amount recognition is presented in this paper. In the training phase, gradient feature is extracted from sliding windows and character HMMs are trained with single character images. In the recognition phase, the text line image is segmented using sentence HMM, which is constructed by character HMMs according to a strict language model. The...
We present an offline signature verification system using three different pseudo-dynamic features, two different classifier training approaches and two datasets. One of the most difficult problems of off-line signature verification is that the signature is just a static image while losing a lot of useful dynamic information. Three separate pseudo-dynamic features based on gray level: local binary...
Gabor filters can extract multi-orientation and multiscale features from face images. Researchers have designed different ways to use the magnitude of the filtered results for face recognition: Gabor Fisher classifier exploited only the magnitude information of Gabor magnitude pictures (GMPs); Local Gabor Binary Pattern uses only the gradient information. In this paper, we regard GMPs as smooth surfaces...
A method for writer-independent off-line handwritten signature verification based on grey level feature extraction and Real Adaboost algorithm is proposed. Firstly, both global and local features are used simultaneously. The texture information such as co-occurrence matrix and local binary pattern are analyzed and used as features. Secondly, Support Vector Machines (SVMs) and the squared Mahalanobis...
An efficient and fast method for vehicle license plate detection in complex background is proposed in this paper. It uses several convolution pattern filters to enhance character strokes while reducing irrelevant edges and background noise. Experimental results show that our proposed method has very high detection accuracy and low false positive rate compared with former methods based on edge detection...
A method for writer-independent off-line handwritten signature verification based on grey level feature extraction and Real Adaboost algorithm is proposed. Firstly, both global and local features are used simultaneously. Secondly, dissimilarity vector is adopted. Finally, Real Adaboost algorithm is applied. Experiments on the public signature database GPDS Corpus show that our proposed method has...
3-D model based objects matching is a fundamental in image processing and computer vision, especially for object localization, tracking, and recognition. In this paper a new deformable models with commonly 9-12 length-angle shape parameters are used for matching, which can represent rich shape details for traffic vehicle classification. A Weighted Modified Square Haudsorff Distance (WMSHD) is designed...
A new method of logo detection in document images is proposed in this paper. It is based on the boundary extension of feature rectangles of which the definition is also given in this paper. This novel method takes advantage of a layout assumption that logos have background (white spaces) surrounding it in a document. Compared with other logo detection methods, this new method has the advantage that...
A novel character line segmentation method for degraded binary images based on feature clustering is proposed in this paper. The application of this research is to segment character lines on images of IC chip surfaces. First, several cutting lines are detected and every two neighbor cutting lines define a candidate character line (CCL). Second, the feature of each CCL is extracted and clustering is...
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