206873031
Lossy compression of images using logic minimization
A technique for lossy compression of images is presented, utilizing ideas of logic minimization. The approach specifically addresses the compression of the binary image data originated in block truncation coding (BTC). The binary vector corresponding to a block of 4/spl times/4 pixels is treated as the output of a Boolean function and prime cubes are generated. The largest prime cube is encoded. Bit rate less than 1.5 bits/pel is attained in BTC without many perceivable errors in the reconstructed grey scale image. Training, pre-stored tables or codebooks, and prior knowledge of the image source are not required by the technique which uses simple logic operations. Computational simplicity of the algorithm makes it suitable for VLSI implementation. Potential of the technique in attaining a rate less than 0.5 bit/pel by applying it on image sequences and extending to blocks of larger size is indicated.
16922921
Wire space estimation and routability analysis
This paper presents a new stochastic model for two-dimensional layouts of large size. Two problems are addressed. (1) Under the condition that the number of wires emanating from a block is Poisson distributed, determine the distribution of channel width, thus estimating the average channel width. (2) Given T tracks for each channel, determine the success probability of routing an M/spl times/M cell array chip. For both problems, closed formulas are obtained. The experiment demonstrates the effectiveness of our approach. The results can be applied to gate array, field-programmable gate array design, etc.
44707452
Diagnosis of clustered faults for identical degree topologies
Huang et al, [1998] studied the diagnosis of clustered faults and wafer testing. They proposed a diagnosis algorithm for a probabilistic fault model in simple rectangular grid structures. In this paper, we extend their results and study the diagnosis algorithm for arbitrary identical degree topologies. Our results are useful and valid for a large class of topologies. We investigate the local and global performance of the algorithm under several important fault distributions: Bernoulli failure distribution, Gamma failure distribution, and exponential failure distribution. We demonstrate that the diagnosis scheme can identify almost all nodes successfully even if the percentage of fault-free units is low (much lower than 50%) while almost all units are guaranteed to be correctly identified. In addition, we show that the performance of the algorithm is insensitive to the changes of the percentage.
40338116
Solving Boolean Equations Using ROSOP Forms
Boolean equations are important tools in digital logic. Previous algorithms for solving Boolean equations are based on the Boolean algebra of disjoint SOP forms. In this paper, we develop a new Boolean algebra with more efficient Boolean operation algorithms, called the reduced ordered SOP (ROSOP) forms, which are canonical representations. ROSOPs are closely related to the well-known OBDD data structure. The results here also show the algebraic structure of OBDDs.
45767095
A Color Image Segmentation Algorithm by Using Region and Edge Information
A novel segmentation algorithm for natural color image is proposed. Fibonacci Lattice-based Sampling is used to get the symbols of image so as to make each pixel’s label containing color information rather than only as a class marker. Next, Region map is formed based on Fibonacci Lattice symbols to depict homogeneous regions. On the other hand, by applying fuzzy homogeneity algorithm on the image, we filter it to acquire Edge map. To strengthen the ability of discrimination, both the weighted maps are combined to form Region-Edge map. Based on above processes, growing-merging method is used to segment the image. Finally, experiments show very promising results.
14692168
Testbed implementation of delay/fault-tolerant mobile sensor network (DFT-MSN)
In this paper we present a testbed implementation of delay/fault-tolerant mobile sensor network (DFT-MSN) for pervasive information gathering. We develop a simple and efficient data delivery scheme tailored for DFT-MSN, which consists of two key components for data transmission and queue management, respectively. The former makes decision on when and where to transmit data messages based on the delivery probability, which reflects the likelihood that a sensor can deliver data messages to the sink. The latter decides which messages to transmit or drop based on the fault tolerance, which indicates the importance of the messages. We implement the proposed data delivery scheme and establish a DFT-MSN testbed by using Crossbow sensors. A small scale experiment is carried out, which shows the effectiveness and efficiency of DFT-MSN
3331857
Table Detection via Probability Optimization
In this paper, we define the table detection problem as a probability optimization problem. We begin, as we do in our previous algorithm, finding and validating each detected table candidates. We proceed to compute a set of probability measurements for each of the table entities. The computation of the probability measurements takes into consideration tables, table text separators and table neighboring text blocks. Then, an iterative updating method is used to optimize the page segmentation probability to obtain the final result. This new algorithm shows a great improvement over our previous algorithm. The training and testing data set for the algorithm include 1, 125 document pages having 518 table entities and a total of 10, 934 cell entities. Compared with our previous work, it raised the accuracy rate to 95.67% from 90.32% and to 97.05% from 92.04%.
18778381
Block truncation coding with adaptive decimation and interpolation
A modification of block truncation coding (BTC) is proposed in this paper. The modification is with a novel adaptive decimation and interpolation method, and predictive entropy coding of the quantization data. The decimation algorithm is designed based on the directional gradients of image blocks so as (1) to preserve the edge information, (2) to enable the interpolator utilize the already reconstructed data in decoder and (3) to better predict the mean value of a block. The quantization data is not directly coded by the two reconstruction levels, but by the block mean and the difference between the block mean and the lower reconstruction level, to further reduce the bit-rate. Compared to other interpolative methods, the new decimation and interpolation method substantially improves the image quality and removes the annoying blocky artifact at the same time. The proposed scheme, which has low computational complexity, is shown to have comparable or better performance to/than BTC methods combined with vector quantization/discrete cosine transform and the most recently BTC modification that utilize the inter-block correlation.
1568939
Robust key establishment in sensor networks
Secure communication guaranteeing reliability, authenticity, and privacy in sensor networks with active adversaries is a challenging research problem since asymmetric key cryptosystems are not suitable for sensor nodes with limited computation and communication capabilities. In most proposed secure communication protocols, sensor nodes need to contact the base station to get a session key first if two sensor nodes want to establish a secure communication channel (e.g., SPINS). In several environments, this may be impractical. In this paper, we study key agreement protocols for which two sensor nodes (who do not necessarily have a shared key from the key predistribution phase) could establish a secure communication channel against active adversaries (e.g., denial of service attacks) without the involvement of the base station.