34090759
Segmentation of external force field for automatic initialization and splitting of snakes
Active contours or snakes have been extensively utilized in handling image segmentation and classification problems. In traditional active contour models, snake initialization is performed manually by users, and topological changes, such as splitting of the snake, cannot be automatically handled. In this paper, we introduce a new method to solve the snake initialization and splitting problem, based on an area segmentation approach: the external force field is segmented first, and then the snake initialization and splitting can be automatically performed by using the segmented external force field. Such initialization and splitting produces multiple snakes, each of which is within the capture range associated to an object and will be evolved to the object boundary. The external force used in this paper is a gradient vector flow with an edge-preserving property (EPGVF), which can prevent the snakes from passing over weak boundaries. To segment the external force field, we represent it with a graph, and a graph-theory approach can be taken to determine the membership of each pixel. Experimental results establish the effectiveness of the proposed approach.
827639
Segmentation of edge preserving gradient vector flow: an approach toward automatically initializing and splitting of snakes
Active contours or snakes have been extensively utilized in handling image segmentation and classification problems. In traditional active contour models, snake initialization is performed manually by users, and topological changes, such as splitting of the snake, can not be automatically handled. In this paper, we introduce a new method to solve the snake initialization and splitting problem, based on an area segmentation approach: the external force field is segmented first, and then the snake initialization and splitting can be automatically performed by using the segmented external force field. Such initialization and splitting produces multiple snakes, each of which is within the capture range associated to an object and evolved to the object boundary. The external force used in this paper is a gradient vector flow with an edge-preserving property (EPGVF), which can prevent the snakes from passing over weak boundaries. To segment the external force field, we represent it with a graph, and a graph-theory approach can be taken to determine the membership of each pixel. Experimental results establish the effectiveness of the proposed approach.
218270
Cryptanalysis of a multistage encryption system
This paper analyzes the security of a new multistage encryption system (MES) recently proposed in ISCAS'2004. It is found that MES is insecure against a differential chosen-plaintext/ciphertext attack. Experiments are given to support the proposed attack. It is also pointed out that the security of MES against brute-force attacks is not sufficiently high.
32219854
Unsupervised texture segmentation using multiresolution hybrid genetic algorithm
This work approaches the texture segmentation problem by incorporating genetic algorithm and k-mean clustering method within a multiresolution structure. First, a quad-tree structure is constructed and the input image is partition into blocks at different resolution levels. Texture features are then extracted from each block. Based on the texture features, a hybrid genetic algorithm is employed to perform the segmentation. The crossover operator of traditional genetic algorithm is replaced with k-means clustering method while the mutate and select operators are adopted. In the final step, the boundaries and the segmentation result of the current resolution level are propagated down to the next level to act as contextual constraints and the initial configuration of the next level, respectively.
15590248
A Class of Discrete Multiresolution Random Fields and Its Application to Image Segmentation
In this paper, a class of Random Field model, defined on a multiresolution array is used in the segmentation of gray level and textured images. The novel feature of one form of the model is that it is able to segment images containing unknown numbers of regions, where there may be significant variation of properties within each region. The estimation algorithms used are stochastic, but because of the multiresolution representation, are fast computationally, requiring only a few iterations per pixel to converge to accurate results, with error rates of 1-2 percent across a range of image structures and textures. The addition of a simple boundary process gives accurate results even at low resolutions, and consequently at very low computational cost.
5432512
RankSQL: query algebra and optimization for relational top-k queries
This paper introduces RankSQL, a system that provides a systematic and principled framework to support efficient evaluations of ranking (top-k) queries in relational database systems (RDBMS), by extending relational algebra and query optimization. Previously, top-k query processing is studied in the middleware scenario or in RDBMS in a "piecemeal" fashion, i.e., focusing on specific operator or sitting outside the core of query engines. In contrast, we aim to support ranking as a first-class database construct. As a key insight, the new ranking relationship can be viewed as another logical property of data, parallel to the "membership" property of relational data model. While membership is essentially supported in RDBMS, the same support for ranking is clearly lacking. We address the fundamental integration of ranking in RDBMS in a way similar to how membership, i.e., Boolean filtering, is supported. We extend relational algebra by proposing a rank-relational model to capture the ranking property, and introducing new and extended operators to support ranking as a first-class construct. Enabled by the extended algebra, we present a pipelined and incremental execution model of ranking query plans (that cannot be expressed traditionally) based on a fundamental ranking principle. To optimize top-k queries, we propose a dimensional enumeration algorithm to explore the extended plan space by enumerating plans along two dual dimensions: ranking and membership. We also propose a sampling-based method to estimate the cardinality of rank-aware operators, for costing plans. Our experiments show the validity of our framework and the accuracy of the proposed estimation model.
19589601
Single machine scheduling to minimize total compression plus weighted flow cost is NP-hard
Abstract This article analyzes the computational complexity of a single machine scheduling problem to minimize total compression plus weighted flow cost. Vickson [Oper. Res. 28 (1980) 1155–1167] studied this problem and conjectured that it was NP-hard. The complexity of this problem remained open since then. We give a positive answer to this conjecture, showing that this problem is NP-hard.