A remote quick rendering model was put forward, based on both the remote mutual control mode of client-server and 3D-texture mapping volume rendering algorithm, aiming at the procession of some medical images of large...
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A remote quick rendering model was put forward, based on both the remote mutual control mode of client-server and 3D-texture mapping volume rendering algorithm, aiming at the procession of some medical images of large data sets. The experiment proves the validity of the rendering model in meeting the demand of rapid and interactive process of medical images on Internet. Compared to the traditional single-computer hardware setting, this model guarantees higher speed and qualified image quality as well.
In accordance with the outer skin and model segmentation issues in simulated plastic surgery, a simplified axis extraction method based on active window was proposed. The new method simplifies the M-Reps by using prio...
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In accordance with the outer skin and model segmentation issues in simulated plastic surgery, a simplified axis extraction method based on active window was proposed. The new method simplifies the M-Reps by using priori shape information of regions. It is applied to the segmentation of outer skin and model in the plastic surgery simulation. The results show the effectiveness of the proposed method.
A nonlinear image enhancement algorithm based on single scale retinex was proposed. Unlike classical retinex methods estimate the illumination image in a complex way, the proposed algorithm estimates the illumination ...
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A nonlinear image enhancement algorithm based on single scale retinex was proposed. Unlike classical retinex methods estimate the illumination image in a complex way, the proposed algorithm estimates the illumination image approximately, and then compensates the approximate estimation in a nonlinear way. Compared with classical retinex methods, the experimental results show that the proposed method can offer better performance not only in visual enhancement but also in fast processing.
A non-negative matrix factorization (NMF) based latent semantic indexing (LSI) model was introduced for image retrieval. Firstly, a semantic space is constructed using NMF-training algorithm. Then the hidden semantic ...
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A non-negative matrix factorization (NMF) based latent semantic indexing (LSI) model was introduced for image retrieval. Firstly, a semantic space is constructed using NMF-training algorithm. Then the hidden semantic features of the query image are extracted with NMF-testing algorithm. At last, ranking the query in this new semantic space and return some images to the user. The experiments show that the model provides better results than SVD-based LSI model and the one without LSI model.
A simple but effective algorithm which is based on minimizing the maximum discrepancy clustering was presented. Two new metrics of distance between any two triangles is developed. By the new distance metrics, the clus...
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A simple but effective algorithm which is based on minimizing the maximum discrepancy clustering was presented. Two new metrics of distance between any two triangles is developed. By the new distance metrics, the clustering method is easily extended to divide the input mesh into several connected regions. Furthermore, a post-processing algorithm, constrained boundary straightening, was proposed to regularize the shapes of partitioned regions. The experiments show that this two-step solution for mesh segmentation performs well in both region planarity and region shape.
The algorithm converts the images into basic graph and super graph, and then treats the interferential curve as principal curve to detect principal curve in images. In the detection, an improved shortest path algorith...
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The algorithm converts the images into basic graph and super graph, and then treats the interferential curve as principal curve to detect principal curve in images. In the detection, an improved shortest path algorithm and orientation offset algorithm are used, and finally, the detected curve is removed from the original image. The experiments conducted with a variety of text images show that this algorithm is effective for eliminating interferential curve of text in images.
This paper presented a new method to obtain the statistical relation between image features and matching probability. After integrating the Gabor wavelet features and some other parameters as matching area measures, t...
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This paper presented a new method to obtain the statistical relation between image features and matching probability. After integrating the Gabor wavelet features and some other parameters as matching area measures, this paper uses the support vector machine (SVM) classification method to transform the estimation of matching probability problem into a classifying one. The experiments show that the proposed method not only has faster computation speed than the method based on the correlation functions, but also gives a reasonable precise estimation.
An approach based on stroke orientation and asymmetric distribution model about feature parameter was proposed, which incorporates structural feature into statistical strategy. An improvement to the algorithm for extr...
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An approach based on stroke orientation and asymmetric distribution model about feature parameter was proposed, which incorporates structural feature into statistical strategy. An improvement to the algorithm for extracting fork points from skeleton images defends the reliability of stroke extraction. The feature vector for statistical recognition is extracted directly from stroke structure, and the asymmetric distribution model is applied to compute distances. The experimental results indicate that the proposed system is effective to handwritten Chinese character recognition.
An efficient approach of using multi-level wavelet transform and co-occurrence matrix for texture defect detection was proposed. The defective image is firstly decomposed into approximation and detail sub-images at va...
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An efficient approach of using multi-level wavelet transform and co-occurrence matrix for texture defect detection was proposed. The defective image is firstly decomposed into approximation and detail sub-images at various levels by wavelet transform. Then, the co-occurrence matrix features of the detail sub-images are computed and analyzed to decide the appropriate level at which the approximation sub-images are reconstructed into non-texture images for defect detection. The experimental results show that this approach is efficient both in speed and performance.
The purpose of trace reconstruction is to recover information about handwriting sequence from static images of characters, which helps incorporate online methods into offline applications and unify the recognition str...
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The purpose of trace reconstruction is to recover information about handwriting sequence from static images of characters, which helps incorporate online methods into offline applications and unify the recognition strategies of single character and character sequence. A stroke segment-based algorithm was proposed, which is equal to the problem of ordering the stroke segments in nature. Structural graph of stroke segments is extracted from skeleton images, by which the relational graph is created. Trace reconstruction is realized as a globally optimal problem, and the handwriting trace is considered as the path with the totally minimal orientation variance, which can be resolved by searching a Hamiltonian path with minimal cost. The cases of trace reconstruction were analyzed, and the accuracy reaches 93.5% on 200 images. The experimental results indicate the proposed approach is effective to the reconstruction of handwriting traces of handwritten numerals.
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