In this paper we describe the principles and the design issues of MEDIARAD, a platform-independent user-oriented programming environment for developing imaging applications in radiology. The development of such system is motivated by the significant increase, during the last few years, of the demand for computerized medical imaging systems in radiology. This increase is due mainly to the advent of newer imaging modalities, such as magnetic resonance or computerized tomography, as well as to the activation of several radiological Screening Programs for early diagnosis of cancer in most western Countries. MEDIARAD should be useful at least to four different types of users: 1) physicians and radiologists who are the basic users and simply want a computer-aided detection (CAD) system in order to receive help in the diagnostic process; 2) Computer Vision researchers and software developers who look for suitable tools to easily and effortless build their own CAD applications; 3) computer trained physicians, who might want to interact with the system in order to personalize and improve it, and 4) researchers interested mainly in testing specific algorithms during the development and evaluation stages which lead to building a specific imaging application. MEDIARAD has already been used to build a CAD system for detecting clusters of breast microcalcifications in digitized mammograms.
{"title":"MEDIARAD: a Multiplatform software Environment for Developing Imaging Applications in RADiology","authors":"E. Catanzariti, R. Prevete, M. Santoro","doi":"10.1109/CAMP.2005.34","DOIUrl":"https://doi.org/10.1109/CAMP.2005.34","url":null,"abstract":"In this paper we describe the principles and the design issues of MEDIARAD, a platform-independent user-oriented programming environment for developing imaging applications in radiology. The development of such system is motivated by the significant increase, during the last few years, of the demand for computerized medical imaging systems in radiology. This increase is due mainly to the advent of newer imaging modalities, such as magnetic resonance or computerized tomography, as well as to the activation of several radiological Screening Programs for early diagnosis of cancer in most western Countries. MEDIARAD should be useful at least to four different types of users: 1) physicians and radiologists who are the basic users and simply want a computer-aided detection (CAD) system in order to receive help in the diagnostic process; 2) Computer Vision researchers and software developers who look for suitable tools to easily and effortless build their own CAD applications; 3) computer trained physicians, who might want to interact with the system in order to personalize and improve it, and 4) researchers interested mainly in testing specific algorithms during the development and evaluation stages which lead to building a specific imaging application. MEDIARAD has already been used to build a CAD system for detecting clusters of breast microcalcifications in digitized mammograms.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122641112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Pirrone, G. Careri, F. S. Fabiano, A. Gentile, S. Gaglio
Robot vision systems notoriously require large computing capabilities, rarely available on physical devices. Robots have limited embedded hardware, and almost all sensory computation is delegated to remote machines. Emerging gigascale integration technologies offer the opportunity to explore alternative computing architectures that can deliver a significant boost to on-board computing when implemented in embedded, reconfigurable devices. This paper explores the mapping of low level feature extraction on one such architecture, the Georgia Tech SIMD Pixel Processor (SIMPil). The Fast Boundary Web Extraction (fBWE) algorithm is adapted and mapped on SIMPil as a fixed-point, data parallel implementation. Application components and their mapping details are provided in this contribution along with a detailed analysis of their performance.
众所周知，机器人视觉系统需要大量的计算能力，很少在物理设备上可用。机器人的嵌入式硬件有限，几乎所有的感官计算都委托给远程机器。新兴的千兆级集成技术提供了探索替代计算架构的机会，当在嵌入式可重构设备中实现时，这些架构可以显著提升板载计算。本文探讨了低级特征提取在这样一个架构上的映射，佐治亚理工学院SIMD像素处理器(SIMPil)。将快速边界Web提取(Fast Boundary Web Extraction, fBWE)算法映射到SIMPil上，作为一个定点数据并行实现。本文提供了应用程序组件及其映射细节，以及对其性能的详细分析。
{"title":"Real-time low level feature extraction for on-board robot vision systems","authors":"R. Pirrone, G. Careri, F. S. Fabiano, A. Gentile, S. Gaglio","doi":"10.1109/CAMP.2005.44","DOIUrl":"https://doi.org/10.1109/CAMP.2005.44","url":null,"abstract":"Robot vision systems notoriously require large computing capabilities, rarely available on physical devices. Robots have limited embedded hardware, and almost all sensory computation is delegated to remote machines. Emerging gigascale integration technologies offer the opportunity to explore alternative computing architectures that can deliver a significant boost to on-board computing when implemented in embedded, reconfigurable devices. This paper explores the mapping of low level feature extraction on one such architecture, the Georgia Tech SIMD Pixel Processor (SIMPil). The Fast Boundary Web Extraction (fBWE) algorithm is adapted and mapped on SIMPil as a fixed-point, data parallel implementation. Application components and their mapping details are provided in this contribution along with a detailed analysis of their performance.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117224067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite recent turbulence of the digital economy, the information society continues its progress. Information and communication technologies (ICT) are increasingly entering in all aspects of our life and in all sectors, opening a world of unprecedented scenarios where people interact with electronic devices embedded in environments that are sensitive and responsive to the presence of users. These context-aware environments combine ubiquitous information, communication, with enhanced personalization, natural interaction and intelligence. A critical issue, common in most of applications framed inside domotic systems or ambient intelligence, is the approach to automatically detect context from wearable or environmental sensor systems and to transform such information for achieving personalized and adaptive services. Most of the flexible and robust systems use probabilistic detection algorithms that require extensive libraries of training; in this work we experiment with a prototype framework based on intelligent agents skilled to capture user habits, identify requests, and apply the artefact-mediated activity through hybrid approaches, featuring adaptive fuzzy control strategy and biometric techniques.
{"title":"Ambient intelligence framework for context aware adaptive applications","authors":"G. Acampora, V. Loia, M. Nappi, S. Ricciardi","doi":"10.1109/CAMP.2005.9","DOIUrl":"https://doi.org/10.1109/CAMP.2005.9","url":null,"abstract":"Despite recent turbulence of the digital economy, the information society continues its progress. Information and communication technologies (ICT) are increasingly entering in all aspects of our life and in all sectors, opening a world of unprecedented scenarios where people interact with electronic devices embedded in environments that are sensitive and responsive to the presence of users. These context-aware environments combine ubiquitous information, communication, with enhanced personalization, natural interaction and intelligence. A critical issue, common in most of applications framed inside domotic systems or ambient intelligence, is the approach to automatically detect context from wearable or environmental sensor systems and to transform such information for achieving personalized and adaptive services. Most of the flexible and robust systems use probabilistic detection algorithms that require extensive libraries of training; in this work we experiment with a prototype framework based on intelligent agents skilled to capture user habits, identify requests, and apply the artefact-mediated activity through hybrid approaches, featuring adaptive fuzzy control strategy and biometric techniques.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115339597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this contribution we present a software system for image processing and image analysis (PUMA) and compare it to other free software systems for this purpose. The system has been developed over a decade and several applications are reported. The system can be used in various modes: over the Internet, via GIMP plugins, via a simple graphical interface, using commandline or scripting tools, and as an application programmer's library.
{"title":"Design of AN IMage AnaLysis system","authors":"D. Paulus, Timo Dickscheid, K.-D. Berg","doi":"10.1109/CAMP.2005.20","DOIUrl":"https://doi.org/10.1109/CAMP.2005.20","url":null,"abstract":"In this contribution we present a software system for image processing and image analysis (PUMA) and compare it to other free software systems for this purpose. The system has been developed over a decade and several applications are reported. The system can be used in various modes: over the Internet, via GIMP plugins, via a simple graphical interface, using commandline or scripting tools, and as an application programmer's library.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114641556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a real-time image stabilization method, based on a 2D motion model and different levels of parallel implementation. This stabilization method is decomposed into three main parts. First, the image matching is determined by a feature-based technique, then the motion between consecutive frames is estimated and filtered to extract the unwanted motion component. This component is finally used to correct (warp) the images, resulting in a stable sequence. To validate our stabilization approach in a real-time on-board system context, the algorithm was implemented and tested over different hardware platforms, allowing a performance evaluation in function of the adopted architecture. In this paper, we present some of the results, concerning the parallel implementation of the algorithm, using the MW ALTIVEC/spl reg/ instructions set, a symmetric multi-processor (SMP) architecture and MIMD-DM architecture.
{"title":"SIMD, SMP and MIMD-DM parallel approaches for real-time 2D image stabilization","authors":"J. Derutin, Fabio Dias, L. Damez, N. Allezard","doi":"10.1109/CAMP.2005.48","DOIUrl":"https://doi.org/10.1109/CAMP.2005.48","url":null,"abstract":"We present a real-time image stabilization method, based on a 2D motion model and different levels of parallel implementation. This stabilization method is decomposed into three main parts. First, the image matching is determined by a feature-based technique, then the motion between consecutive frames is estimated and filtered to extract the unwanted motion component. This component is finally used to correct (warp) the images, resulting in a stable sequence. To validate our stabilization approach in a real-time on-board system context, the algorithm was implemented and tested over different hardware platforms, allowing a performance evaluation in function of the adopted architecture. In this paper, we present some of the results, concerning the parallel implementation of the algorithm, using the MW ALTIVEC/spl reg/ instructions set, a symmetric multi-processor (SMP) architecture and MIMD-DM architecture.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125380936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a real-time system for moving object and obstacle detection (MOOD) based on stereo vision. A disparity map is calculated to have a 3D representation of the scene and to recognize obstacles. The best methods in literature have been employed and opportunely modified to obtain the best compromise between the high frame-rate and the high accuracy requirements. An efficient algorithm for motion vector analysis, based on optical flow, is used to segment moving objects and obstacles. The application domain is automatic vehicle guidance (AVG) and autonomous mobile robots (AMR), in which a stereo vision system is applied on board. Results are presented with reference to a synthetic database created ad hoc to evidence some interesting cases of object/obstacle trajectories.
{"title":"A real-time stereo-vision system for moving object and obstacle detection in AVG and AMR applications","authors":"P. Foggia, A. Limongiello, M. Vento","doi":"10.1109/CAMP.2005.6","DOIUrl":"https://doi.org/10.1109/CAMP.2005.6","url":null,"abstract":"This paper presents a real-time system for moving object and obstacle detection (MOOD) based on stereo vision. A disparity map is calculated to have a 3D representation of the scene and to recognize obstacles. The best methods in literature have been employed and opportunely modified to obtain the best compromise between the high frame-rate and the high accuracy requirements. An efficient algorithm for motion vector analysis, based on optical flow, is used to segment moving objects and obstacles. The application domain is automatic vehicle guidance (AVG) and autonomous mobile robots (AMR), in which a stereo vision system is applied on board. Results are presented with reference to a synthetic database created ad hoc to evidence some interesting cases of object/obstacle trajectories.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126631718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G. D. Ruvo, P. D. Ruvo, F. Marino, G. Mastronardi, P. Mazzeo, E. Stella
Rail inspection is a very important task in railway maintenance and it is periodically needed for preventing dangerous situations. Inspection is operated manually by trained human operator walking along the track searching for visual anomalies. This monitoring is unacceptable for slowness and lack of objectivity, because the results are related to the ability of the observer to recognize critical situations. The paper presents a prototypal FPGA-based architecture which automatically detects presence/absence of the fastening bolts that fix the rails to the sleepers. A simple predicting algorithm, exploiting the geometry of the railways, extracts, from the long video sequence acquired by a digital line scan camera, few windows where the presence of bolts is expected. These windows are preprocessed according to a Haar transform and then provided to a multilayer perceptron neural classifiers (MLPNCs) which reveals the presence/absence of the fastening bolts with an accuracy of 99.6% in detecting visible bolts and of 95% in detecting missing bolts. A FPGA-based architecture performs these tasks in 13.29 /spl mu/s, allowing an on-the-fly analysis of a video sequence acquired up at 190 km/h.
{"title":"A FPGA-based architecture for automatic hexagonal bolts detection in railway maintenance","authors":"G. D. Ruvo, P. D. Ruvo, F. Marino, G. Mastronardi, P. Mazzeo, E. Stella","doi":"10.1109/CAMP.2005.4","DOIUrl":"https://doi.org/10.1109/CAMP.2005.4","url":null,"abstract":"Rail inspection is a very important task in railway maintenance and it is periodically needed for preventing dangerous situations. Inspection is operated manually by trained human operator walking along the track searching for visual anomalies. This monitoring is unacceptable for slowness and lack of objectivity, because the results are related to the ability of the observer to recognize critical situations. The paper presents a prototypal FPGA-based architecture which automatically detects presence/absence of the fastening bolts that fix the rails to the sleepers. A simple predicting algorithm, exploiting the geometry of the railways, extracts, from the long video sequence acquired by a digital line scan camera, few windows where the presence of bolts is expected. These windows are preprocessed according to a Haar transform and then provided to a multilayer perceptron neural classifiers (MLPNCs) which reveals the presence/absence of the fastening bolts with an accuracy of 99.6% in detecting visible bolts and of 95% in detecting missing bolts. A FPGA-based architecture performs these tasks in 13.29 /spl mu/s, allowing an on-the-fly analysis of a video sequence acquired up at 190 km/h.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127471307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. D. Paola, S. Fiduccia, S. Gaglio, L. Gatani, G. Re, A. Pizzitola, M. Ortolani, P. Storniolo, A. Urso
This paper focuses on improving network management by the adoption of artificial intelligence techniques. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as a managing entity capable of directing, coordinating, and triggering monitoring and management actions in the proposed architecture. The logical inference system has been devised to enable automated isolation, diagnosis, and to repair network anomalies, thus enhancing the reliability, performance, and security of the network. The measurements of network events are captured by programmable sensors deployed on the network devices and are collected by the network management entity where they are merged with general domain knowledge, with a view to identifying the root causes of anomalies, and to decide on reparative actions. The relevant results inferred by the logical reasoner and the significant events occurred on the network are stored both in a global DB and in local distributed DBs, in order to enable successive analyses of network events. In order to illustrate the advantages and potential benefits deriving from the reasoning capabilities of our management system, the results of preliminaries experiments are analyzed.
{"title":"Rule based reasoning for network management","authors":"A. D. Paola, S. Fiduccia, S. Gaglio, L. Gatani, G. Re, A. Pizzitola, M. Ortolani, P. Storniolo, A. Urso","doi":"10.1109/CAMP.2005.47","DOIUrl":"https://doi.org/10.1109/CAMP.2005.47","url":null,"abstract":"This paper focuses on improving network management by the adoption of artificial intelligence techniques. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as a managing entity capable of directing, coordinating, and triggering monitoring and management actions in the proposed architecture. The logical inference system has been devised to enable automated isolation, diagnosis, and to repair network anomalies, thus enhancing the reliability, performance, and security of the network. The measurements of network events are captured by programmable sensors deployed on the network devices and are collected by the network management entity where they are merged with general domain knowledge, with a view to identifying the root causes of anomalies, and to decide on reparative actions. The relevant results inferred by the logical reasoner and the significant events occurred on the network are stored both in a global DB and in local distributed DBs, in order to enable successive analyses of network events. In order to illustrate the advantages and potential benefits deriving from the reasoning capabilities of our management system, the results of preliminaries experiments are analyzed.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121584522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
When strong CPU power consumption constraints must be met, and high computation speed is mandatory (realtime processing), it can be preferable to adopt custom hardware for some computationally intensive image processing tasks. An alternative approach to conventional approaches is provided by the Cellular Neural Network (CNN) paradigm. CNNs have been extensively used in image processing applications: in the past, we developed a still image segmentation technique based on an active contour obtained via single-layer CNNs. This technique suffered from sensitivity to noise as most of edge-based methods: noise may create insignificant false edges or determine some "edge fragmentation". The aim of this paper is to re-formulate the algorithm previously proposed in order to step-over the cited weakness. The new formulation is introduced and justified and experimental results are presented. Finally, a competition-based approach for a parameterless version of the presented algorithm is proposed and discussed as an ongoing work.
{"title":"A CNN-based framework for 2D still-image segmentation","authors":"G. Iannizzotto, P. Lanzafame, F. L. Rosa","doi":"10.1109/CAMP.2005.3","DOIUrl":"https://doi.org/10.1109/CAMP.2005.3","url":null,"abstract":"When strong CPU power consumption constraints must be met, and high computation speed is mandatory (realtime processing), it can be preferable to adopt custom hardware for some computationally intensive image processing tasks. An alternative approach to conventional approaches is provided by the Cellular Neural Network (CNN) paradigm. CNNs have been extensively used in image processing applications: in the past, we developed a still image segmentation technique based on an active contour obtained via single-layer CNNs. This technique suffered from sensitivity to noise as most of edge-based methods: noise may create insignificant false edges or determine some \"edge fragmentation\". The aim of this paper is to re-formulate the algorithm previously proposed in order to step-over the cited weakness. The new formulation is introduced and justified and experimental results are presented. Finally, a competition-based approach for a parameterless version of the presented algorithm is proposed and discussed as an ongoing work.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121881261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A hybrid adder-based distributed arithmetic (DA) architecture targeting a reconfigurable system-on-chip (rSoC) platform has been presented. The work exemplifies hardware comparisons of three DA based discrete cosine transform (DCT) algorithms based on pure-RAM, mixed-RAM and CORDIC-based processors. Preliminary investigation involved evaluation of the DCT algorithms on a heterogeneous composition of domain-specific memory and logic building blocks. The architectures were simulated for functional validation on ModelSim SE v6.0 and compliance testing of these architectures was performed using a self-testing testbench. The motivation was to illustrate the modularity, regularity, symmetry, and recursive-decomposition properties of transform vector-matrix computations for a case study of discrete cosine transforms using adder-based DA. Further, the paper overviews existing DCT architectures and previews future reconfigurable computing devices and contributes towards a novel conjecture on future directions in the reconfigurable hardware landscape. The embedded reconfigurable computation array presented in this paper has an intermediate-grain framework unlike the fine-grained nature of the current FPGAs.
针对可重构的片上系统(rSoC)平台，提出了一种基于混合加法器的分布式算法(DA)架构。该工作举例说明了基于纯ram、混合ram和基于cordic处理器的三种基于DA的离散余弦变换(DCT)算法的硬件比较。初步的研究涉及对领域特定内存和逻辑构建块的异构组成的DCT算法的评估。在ModelSim SE v6.0上模拟这些体系结构以进行功能验证，并使用自测测试台执行这些体系结构的遵从性测试。动机是为了说明转换向量矩阵计算的模块化、规则性、对称性和递归分解性质，以使用基于加法器的DA进行离散余弦变换的案例研究。此外，本文概述了现有的DCT架构，并展望了未来的可重构计算设备，并对可重构硬件领域的未来方向做出了新的推测。本文提出的嵌入式可重构计算阵列具有中等粒度的框架，不同于当前fpga的细粒度特性。
{"title":"Embedded reconfigurable DCT architectures using adder-based distributed arithmetic","authors":"A. Pai, K. Benkrid, D. Crookes","doi":"10.1109/CAMP.2005.23","DOIUrl":"https://doi.org/10.1109/CAMP.2005.23","url":null,"abstract":"A hybrid adder-based distributed arithmetic (DA) architecture targeting a reconfigurable system-on-chip (rSoC) platform has been presented. The work exemplifies hardware comparisons of three DA based discrete cosine transform (DCT) algorithms based on pure-RAM, mixed-RAM and CORDIC-based processors. Preliminary investigation involved evaluation of the DCT algorithms on a heterogeneous composition of domain-specific memory and logic building blocks. The architectures were simulated for functional validation on ModelSim SE v6.0 and compliance testing of these architectures was performed using a self-testing testbench. The motivation was to illustrate the modularity, regularity, symmetry, and recursive-decomposition properties of transform vector-matrix computations for a case study of discrete cosine transforms using adder-based DA. Further, the paper overviews existing DCT architectures and previews future reconfigurable computing devices and contributes towards a novel conjecture on future directions in the reconfigurable hardware landscape. The embedded reconfigurable computation array presented in this paper has an intermediate-grain framework unlike the fine-grained nature of the current FPGAs.","PeriodicalId":393875,"journal":{"name":"Seventh International Workshop on Computer Architecture for Machine Perception (CAMP'05)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2005-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124651411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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