1221771
Multi-scale feature identification using evolution strategies
An image usually contains a number of different features and regions. Many image-related applications, such as content-based image retrieval and MRI-based diagnosis, often require the ability to identify and mark features within the image. For images containing a specific sort of feature (e.g. convective storm) or region (e.g. earthquake debris), that feature or region is always located adjacent to other features and regions on the image. A generic framework for automatically identifying features in images based on evolutionary computation is proposed here. The significant characteristic of the method is that it does not require segmentation. We use evolution strategies as the optimization algorithm to identify features. The system is based on a conjecture that certain filters will give prominent responses to certain features. The identified features are represented as regions enclosed within the chosen search structure-the ellipse. By defining filter response criteria as the fitness function, evolution strategies succeeds in finding the feature in a much more efficient way than, say, segmentation.
16151894
Low Level Fusion of Imagery Based on Dempster-Shafer Theory
An approach to fuse multiple images based on Dempster-Shafer evidential reasoning is proposed in this article. Dempster-Shafer theory provides a complete framework for combining weak evidences from multiple sources. Such situations typically arise in the image fusion problems, where a ‘real scene’ image has to be estimated from incomplete and unreliable observations. By converting images from their spatial domain into the evidential representations, decisions are made to aggregate evidences such that a fused image is generated. The proposed fusion approach is evaluated on a broad set of images and promising results are given.
38619191
Function Granularity Estimation for Multimodal Optimization
In this article, we study the subspace function granularity and present a method to estimate the sharing distance and the optimal population size. To achieve multimodal function optimization, niching techniques diversify the population of Evolutionary Algorithms (EA) and encourage heterogeneous convergence to multiple optima. The key to a successful diversification is effective resource sharing. Without knowing the fitness landscape, resource sharing is usually determined by uninformative assumptions on the number of peaks. Using the Probably Approximately Correct (PAC) learning theory and the ∊-cover concept, a PAC neighborhood for a set of samples is derived. Within this neighborhood, we sample the fitness landscape and compute the subspace Fitness Distance Correlation (FDC) coefficients. Using the estimated granularity feature of the fitness landscape, the sharing distance and the population size are determined. Experiments demonstrate that by using the estimated population size and sharing distance an Evolutionary Algorithm successfully identifies multiple optima.
27055322
A Fast Evolution Strategies Based Approach To Image Registration
An image registration approach based on Evolution Strategies is proposed. In image registration, an invariant reference needs to be established within each source image, which is unavailable in many cases. To solve this problem, feature configuration (which is defined as the cluster of feature vectors on an image representing homogeneous feature distribution,) is employed to describe the object inside the scene. Instead of finding the correspondence of the entire image, the spatial relationships of the feature configuration in every source image are discovered with Evolution Strategies (ES). While one approach, even this one, may not be suitable for every image domain, the ES approach has many advantages. Compared to some methods, it is computationally effective; compared to other, it is capable of discovering transformations of larger scope (e.g., greater rotation angles or translation distances etc.) The search structure we use is an ellipsoid. The results from various images prove it to be an efficient and effective method.
223678
Automatic classification of digestive organs in wireless capsule endoscopy videos
Wireless Capsule Endoscopy (WCE) allows a physician to examine the entire small intestine without any surgical operation. With the miniaturization of wireless and camera technologies the ability comes to view the entire gestational track with little effort. Although WCE is a technical break-through that allows us to access the entire intestine without surgery, it is reported that a medical clinician spends one or two hours to assess a WCE video, It limits the number of examinations possible, and incur considerable amount of costs. To reduce the assessment time, it is critical to develop a technique to automatically discriminate digestive organs such as esophagus, stomach, small intestinal (i.e., duodenum, jejunum, and ileum) and colon. In this paper, we propose a novel technique to segment a WCE video into these anatomic parts based on color change pattern analysis. The basic idea is that the each digestive organ has different patterns of intestinal contractions that are quantified as the features. We present the experimental results that demonstrate the effectiveness of the proposed method.
6913478
Validation of code-improving transformations for embeded systems
Programmers of embeded systems often develop software in assembly code due to inadequate support from compilers and the need to meet critical speed and/or space constraints. Many embeded applications are being used as a component of an increasing number of critical systems. While achieving high performance for these systems is important, ensuring that these systems execute correctly is vital. One portion of this process is to ensure that code-improving transformations applied to a program will not change the program's semantic behavior, which may be jeopardized when transformations are specified manually. This paper describes a general approach for validation of many low-level code-improving transformations made either by a compiler or specified by hand. Initially, we associate a region of the program representation with a code-improving transformation. Afterwards, we calculate the region's effects on the rest of the program before and after the transformation. The transformation is considered valid when the effects before and after the transformation are identical. We implemented an automatic validation system in the vpo compiler. The system is currently able to validate all code-improving transformations in vpo except transformations that affect blocks across loop levels.
33631313
Particle Swarm Optimization with Multiscale Searching Method
This paper presents a new method for effectively searching all global minima of a multimodal function. The method is based on particle swarm optimizer, particles are dynamically divided into serval subgroups of different size in order to explore variable space using various step size simultaneously. In each subgroup, a new scheme is proposed to update the the positions of particles, this scheme takes into consideration the effect of all subgroup seeds. Experimental results for one dimensional, two dimensional and thirty dimensional test suites demonstrated that this method can get overall promising performance over a wide range problems.
9140729
INSPIRE: an interactive image assisted non-photorealistic rendering system
We present a GPU supported interactive non-photorealistic rendering system, INSPIRE, which performs feature extraction in both image space, on intermediately rendered images, and object space, on models of various representations, e.g., point, polygon, or hybrid models, without needing connectivity information. INSPIRE obtains interactive NPR rendering with most styles of existing NPR systems, but offers more flexibility on model representations and compromises little on rendering speed.
33385860
An empirical study of reliable multicast protocols over Ethernet-connected networks
Recent advances in multicasting over the Internet present new opportunities for improving communication performance for clusters of workstations. Realizing collective communication over reliable multicast can achieve higher performance than over reliable unicast primitives. The standard IP multicast, however, only supports unreliable multicast, which is difficult to use for building high level message passing routines. Thus, reliable multicast primitives must be implemented over the standard IP multicast to facilitate the use of multicast for high-performance communication on clusters of workstations. Although many reliable multicast protocols have been proposed for the wide area Internet environment, the impact of special features of local area networks (LANs) on the performance of the reliable multicast protocols has not been thoroughly studied. Efficient reliable multicast protocols for LANs must exploit these features to achieve the best performance. In this paper, we present our implementation of four types of reliable multicast protocols: the ACK-based protocols, the NAK-based protocols with polling, the ring-based protocols and the tree-based protocols. The protocols are implemented over IP multicast using the standard UDP interface. We evaluate the performance of the protocols over Ethernet-connected networks, study the impact of some special features of the Ethernet on the performance of the protocols and investigate the methods to exploit these features to improve communication performance.
14733597
Automatic Validation of Code-Improving Transformations
Programmers of embedded systems often develop software in assembly code due to critical speed and/or space constraints and inadequate support from compilers. Many embedded applications are being used as a component of an increasing number of critical systems. While achieving high performance for these systems is important, ensuring that these systems execute correctly is vital. One portion of this process is to ensure that code-improving transformations on a program will not change the program's semantic behavior. This paper describes a general approach for validation of many low-level code-improving transformations made either by a compiler or specified by hand.