A system of map structure recognition and automatic map data acquisition was proposed. This system is based on binary skeleton image which is firstly obtained from scanned maps. Basic graph and super graph are propose...
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A system of map structure recognition and automatic map data acquisition was proposed. This system is based on binary skeleton image which is firstly obtained from scanned maps. Basic graph and super graph are proposed to facilitate the processing. Then kinds of interferential structures are analyzed and the corresponding removal methods are also introduced. Finally, the breaking point method is presented to polygonalize the house/building graph. The experiments conducted with various maps prove that the system is robust and effective to deal with complex scanned paper maps and can generate vector map automatically and correctly.
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.
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 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.
Based on the statistic and the fuzzy uncertainty information in an image, a new fuzzy information gain method was proposed to measure the distinctness between the object image and the reference image, which provides a...
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Based on the statistic and the fuzzy uncertainty information in an image, a new fuzzy information gain method was proposed to measure the distinctness between the object image and the reference image, which provides a new criterion for image matching or retrieval. The experimental results demonstrate the effectiveness of the new method.
Many problems in image representation and classification involve some form of dimensionality reduction. Nonnegative matrix factorization （NMF） is a recently proposed unsupervised procedure for learning spatially loc...
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Many problems in image representation and classification involve some form of dimensionality reduction. Nonnegative matrix factorization （NMF） is a recently proposed unsupervised procedure for learning spatially localized, partsbased subspace representation of objects. An improvement of the classical NMF by combining with Log-Gabor wavelets to enhance its part-based learning ability is presented. The new method with principal component analysis （PCA） and locally linear embedding （LIE） proposed recently in Science are compared. Finally, the new method to several real world datasets and achieve good performance in representation and classification is applied.
This paper investigated the performances of a well-known car-following model with numerical simulations in describing the deceleration process induced by the motion of a leading car. A leading car with a pre-specilied...
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This paper investigated the performances of a well-known car-following model with numerical simulations in describing the deceleration process induced by the motion of a leading car. A leading car with a pre-specilied speed profile was used to test the above model. The results show that this model is to some extent deficient in performing the process aforementioned. Modifications of the model to overcome these deficiencies were demonstrated anda modified car-following model was proposed accordingly. Furthermore, the delay time of car motion of the new model were studied.
This paper presents a level of detail (LOD) selection algorithm for multi-resolution volume rendering using 3D texture mapping. It uses an adaptive scheme that renders the volume in a region-of-interest at a high reso...
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Based on the study of the characteristics of humans' vision system, this paper designed a new algorithm of medical image compression and combined the masking feature of human vision system and the three component ...
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Based on the study of the characteristics of humans' vision system, this paper designed a new algorithm of medical image compression and combined the masking feature of human vision system and the three component model of the image. The experiments were done on the medical images including CT and MRI. The results show that under the same compression ratio, the method used in the paper can achieve better subjective visual quality. The compression ratio can reach 16:1, if the visually lossless effect is required, i.e., almost all the relevant medical information is reserved.
In this paper, a line-based scan image compression algorithm with low complexity was presented. The algorithm was based on Christos Chrysalis's line-based wavelet transformation coding. There was not image tiling ...
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In this paper, a line-based scan image compression algorithm with low complexity was presented. The algorithm was based on Christos Chrysalis's line-based wavelet transformation coding. There was not image tiling in the algorithm. The supposed algorithm modeled with contexts for different subband after quantifying wavelet coefficients uniformly. A modified Golomb-Rice algorithm with low complexity was adopted as entropy coder. The experiment shows that the memory requirement of the algorithm is far less than that of the SPIHT in compressing images with huge size. The complexity of the entropy coding of the algorithm is reduced largely. The algorithm is especially appropriate for remote sensing image compression system with power and space limited.
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