We propose a direct image segmentation algorithm in the JPEG compressed domain. The algorithm features extracting statistical parameters from direct cosine transform (DCT) coefficients without its inverse transform, a...
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We propose a direct image segmentation algorithm in the JPEG compressed domain. The algorithm features extracting statistical parameters from direct cosine transform (DCT) coefficients without its inverse transform, and growing regions in line with JPEG compression seamlessly in blocks of 8 x 8 pixels. In comparison with the latest research efforts in region-based image segmentation, our proposed algorithm achieves significant advantages, including (1) no iteration is involved, (2) no full decompression is required, and (3) segmentation performance is competitive. (C) 2003 SPIE and IST.
Defining criteria to determine precisely the boundaries of masses in mammograms is a difficult task. The problem is compounded by the fact that most malignant tumors possess fuzzy boundaries with a slow and extended t...
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Defining criteria to determine precisely the boundaries of masses in mammograms is a difficult task. The problem is compounded by the fact that most malignant tumors possess fuzzy boundaries with a slow and extended transition from a dense core region to the surrounding less-dense tissues. We propose two segmentation methods that incorporate fuzzy concepts. The first method determines the boundary of a mass or tumor by region growing after a preprocessing step based on fuzzy sets to enhance the region of interest (ROI). Contours provided by the method have demonstrated a good match with the contours drawn by a radiologist, as indicated by good agreement between the two sets of contours for 47 mammograms. The second segmentation method is a fuzzy region-growing method that takes into account the uncertainty present around the boundaries of tumors. The difficult step of deciding on a crisp boundary is obviated in the proposed method. Measures of inhomogeneity computed from the pixels present in a suitably defined fuzzy ribbon have indicated potential use in classifying the masses and tumors as benign or malignant, with a sensitivity of 0.8 and a specificity of 0.9. (C) 2003 SPIE and IST.
We propose a heuristic approach to color quantize images with contextual information taken into consideration. The idea is to locate the regions of an image having the greatest need for colors, and allocate more quant...
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We propose a heuristic approach to color quantize images with contextual information taken into consideration. The idea is to locate the regions of an image having the greatest need for colors, and allocate more quantization levels to them. We achieve this by scanning the elements of the input image in a way determined by their local intensity and selecting the color representatives that comprise the color map according to their local popularity. The overall performance of the color quantization algorithm is evaluated on a representative set of artificial and real images. The experimental results indicate good performance of our proposed algorithm with the capability to focus on the regions of an image having important color information. (C) 2003 SPIE and IST.
Modified implementations of simulated annealing (SA) for image segmentation are proposed and evaluated. The segmentation procedure is based on a Markov random field (MRF) model for describing regions within an image. ...
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Modified implementations of simulated annealing (SA) for image segmentation are proposed and evaluated. The segmentation procedure is based on a Markov random field (MRF) model for describing regions within an image. SA offers an iterative approach for computing a set of labels with maximum a posteriori (MAP) probability. However, this approach is computationally expensive and lacks robustness in noisy environments. We propose a random cost function (RCF) for computing a posterior energy function in SA. The proposed modified SA (SA-RCF) method depicts more robust performance for image segmentation than standard SA at the same computational cost. Alternatively, we proposed a multi-resolution (MR) approach based on MRF which offers robust segmentation for noisy images with significant reduction in the computational cost. Computational cost and segmentation accuracy of each algorithm were examined using a set of simulated head computerized tomography (CT) phantoms. (C) 2003 SPIE and IST.
This paper introduces a new class of bases, called bandelet bases, which decompose the image along multiscale vectors that are elongated in the direction of a geometric flow. This geometric flow indicates the directio...
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ISBN:
(纸本)0819450235
This paper introduces a new class of bases, called bandelet bases, which decompose the image along multiscale vectors that are elongated in the direction of a geometric flow. This geometric flow indicates the direction in which the image grey levels have regular variations. The image decomposition in a bandelet basis is implemented with a fast subband filtering algorithm. Bandelet bases lead to optimal approximation rates for geometrically regular images. For image compression, the bandelet basis geometry is optimized with a fast best basis algorithm. Comparisons are made for image compression with wavelet bases.
Feature extraction is a critical preprocessing step, which influences the outcome of the entire process of developing significant metrics for medical image evaluation. The. purpose of this paper is firstly to compare ...
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ISBN:
(纸本)0819448338
Feature extraction is a critical preprocessing step, which influences the outcome of the entire process of developing significant metrics for medical image evaluation. The. purpose of this paper is firstly to compare the effect of an optimized statistical feature extraction methodology to a well-designed combination of point operations for feature extraction at the preprocessing stage of retinal images for developing useful diagnostic metrics for retinal diseases such as glaucoma and diabetic retinopathy. Segmentation of the extracted features allows us to investigate the effect of occlusion induced by these features on generating stereo disparity mapping and 3-D visualization of the optic cup/disc. Segmentation of blood vessels in the retina also has significant application in generating precise vessel diameter metrics in vascular diseases such as hypertension and diabetic retinopathy for monitoring progression of retinal diseases.
This paper introduces a method for the automatic discrimination of digital images based on their semantic content. The proposed system allows to detect if a digital image contains or not a text. This is realized by a ...
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ISBN:
(纸本)0819448176
This paper introduces a method for the automatic discrimination of digital images based on their semantic content. The proposed system allows to detect if a digital image contains or not a text. This is realized by a multi-steps procedure based on low-level features set properly derived. Our experiments show that the proposed algorithm is competitive in efficiency with classical techniques, and it has a lower complexity.
Document structure analysis can be regarded as a syntactic analysis problem. The order and containment relations among the physical or logical components of a document page can be described by an ordered tree structur...
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ISBN:
(纸本)0819448109
Document structure analysis can be regarded as a syntactic analysis problem. The order and containment relations among the physical or logical components of a document page can be described by an ordered tree structure and can be modeled by a tree grammar which describes the page at the component level in terms of regions or blocks. This paper provides a detailed survey of past work on document structure analysis algorithms and summarize the limitations of past approaches. In particular, we survey past work on document physical layout representations and algorithms, document logical structure representations and algorithms, and performance evaluation of document structure analysis algorithms. In the last section, we summarize this work and point out its limitations.
This paper presents various architectural options for implementing a K-Means Re-Clustering algorithm suitable for unsupervised segmentation of hyperspectral images. Performance metrics are developed based upon quantit...
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ISBN:
(纸本)081944801X
This paper presents various architectural options for implementing a K-Means Re-Clustering algorithm suitable for unsupervised segmentation of hyperspectral images. Performance metrics are developed based upon quantitative comparisons of convergence rates and segmentation quality. A methodology for making these comparisons is developed and used to establish K values that produce the best segmentations with minimal processing requirements. Convergence rates depend on the initial choice of cluster centers. Consequently, this same methodology may be used to evaluate the effectiveness of different initialization techniques.
This paper describes a preliminary study aimed at improving the quality of soft-blue veined cheeses by the use of magnetic resonance images analysis. MRI measurements were performed on thirty-two samples from two diff...
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ISBN:
(纸本)0819449989
This paper describes a preliminary study aimed at improving the quality of soft-blue veined cheeses by the use of magnetic resonance images analysis. MRI measurements were performed on thirty-two samples from two different processing conditions and at three different stages from day 3 after the production to day 37. A segmentation algorithm based on a Self Organizing Map was used to segment the images into six classes. A cavity extraction was then performed. A principal component analysis was computed on variables corresponding to the cavities surface distribution. The results pointed out differences between the two types of cheeses, particularly for day 3 and day 37. This confirmed the interest to use MRI to analyze such products. Further investigations are planned for the analysis of other characteristics of the cheeses and other methods of segmentation.
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