In this paper, a methodology for designing the architecture of the processor array for wide class of image processing algorithms is proposed. A concept of spatially expanding the SFG description which enables us to handle the problem as merely one-dimensional signal processing is used in constructing the methodology. Problem of I/O interface which is critical in real-time processing is also considered.

A novel Template Updating system for fingerprint verification systems used in mobile applications is introduced in the paper. Based on the proposed method, the system performance is improved much more than the original one. Not only the FRR (False Reject Rate) but also the small overlap problem caused by the very narrow sensor on the mobile phone are solved. Based on the template updating system, templates are replaced with matched inputs towards a target structure which can expand the coverage of templates with large displacement and rotation. By using the test database, the system performance shows the FRR can be reduced by 79% in comparison with the one without template updating procedure. This system was adopted in practical mobile phones in the commercial market in 2009.

A simple extension used to assist the decomposition of task-level concurrency within C programs is presented in this paper. The concurrency decomposition is meant to be used as the point of entry for Multiprocessor System-on-Chips (MPSoC) architectures' design-flow. Our methodology allows the (re)use of readily available reference C programs and enables easy and rapid exploration for various alternatives of task partitioning strategies; a crucial task that greatly influences the overall quality of the designed MPSoC. A test case using a JPEG encoder application has been performed and the results are presented in this paper.

In this paper, a dedicated hardware design for motion estimation LSI of MPEG2 is presented. Combining our bits truncation adaptive pyramid (BTAP) algorithm with Window-MSPA architecture, the hardware cost is tremendously reduced without PSNR performance degradation for mean pyramid algorithm. The core of the test chip working at 83 MHz, performs a search range of 67 for image size of 1920 1152 and achieves video rate of 60 field/s. It can be used for HDTV purpose. The chip size is 4. 8 mm 4. 8 mm with 0. 5u 2-level metal CMOS technology. The result in this paper shows our promising future to realize one chip HDTV MPEG2 encoder.

Ultra-wideband (UWB) technology has attracted much attention recently due to its high data rate and low emission power. Its media access control (MAC) protocol, WiMedia MAC, promises a lot of facilities for high-speed and high-quality wireless communication. However, these benefits in turn involve a large amount of computational load, which challenges the traditional uniprocessor architecture based implementation method to provide the required performance. However, the constrained cost and power budget, on the other hand, makes using commercial multiprocessor solutions unrealistic. In this paper, a low-cost and energy-efficient multiprocessor system-on-chip (MPSoC), which tackles at once the aspects of system design, software migration and hardware architecture, is presented for the implementation of UWB MAC layer. Experimental results show that the proposed MPSoC, based on four simple RISC processors and shared-memory infrastructure, achieves up to 45% performance improvement and 65% power saving, but takes 15% less area than the uniprocessor implementation.

In recent years, there is an increasing trend of using biometric identifiers for personal authentication. Encouraged by advances in smart card technologies, the fingerprint matching gets increasingly embedded into smart cards for an effective personal authentication method. However, current generation of low cost smart cards are usually equipped with limited hardware resources such as an 8-bit or 16-bit microcontroller. The fingerprint matching typically is a time consuming, computationally intensive and costly process. Therefore, it is still a challenge to integrate the fingerprint matching into a smart card. In this paper, we present a fast memory-efficient fingerprint matching using minutia ridge shape feature. This feature offers advantages of smaller template size, smaller memory requirement, faster matching time and robust matching against image distortion over conventional minutiae-based feature. The implementation result shows that the proposed method can be embedded in smart cards for a real-time Match-on-Card system.

A new H.263+ rate control method that has very low encoder-decoder delay, small buffer and low computational complexity for hardware realization is proposed in this paper. This method focuses on producing low encoder-decoder delay in order to solve the lip synchronization problem. Low encoder-decoder delay is achieved by improving target bit rate achievement and reducing processing delay. The target bit rate achievement is improved by allocating an optimum frame encoding bits, and employing a new adaptive threshold of zero vector motion estimation. The processing delay is reduced by simplifying quantization parameter computation, applying a new non-zero coefficient distortion measure and utilizing previous frame information in current frame encoding. The simulation results indicate very large number skipped frames reduction in comparison with the test model TMN8. There were 80 skipped frames less than that of TMN8 within a 380 frame sequence during encoding of a very high movement video sequence. The 27 kbps target bit rate is achieved with insignificant difference for various types of video sequences. The simulation results also show that our method successfully allocates encoding bits, maintains small data at the encoder buffer and avoids buffer from overflow and underflow.

A further study on a VLSI system compiler, named VEGA (VLSI Embodiment for General Algorithms), is presented. It maps a general digital signal processing algorithm onto a neo-systolic array, which is a VLSI oriented multiprocessor array. Highly complicated mapping problem is divided into subproblems such as modularization, operation grouping, processor placement, scheduling, control logic synthesis, and mask pattern generation. In this paper, the modularization technique is proposed which homogenizes all the operations of the processing algorithm to multiply-add operations. The processor placement algorithm to map processing algorithm onto a neo-systolic array so as to minimize data transfer time is also proposed.

The paper presents the improvement of out new approach to optimize the process parameter variation, device heat and wire parasitics for analog LSI design by explicitly incorporating various performance estimations into objective functions for placement and routing. To minimize these objective functions, the placement by the simulated annealing method, and maze routing are effectively modified with the perfomance estimation. The improvement results in the excellent performance driven layout for the large size of analog LSIs.

We present distributed load balancing mechanisms implemented on multiprocessor systems for real time video encoding, which dynamically equalize load amounts among PE's to cope with extensive computing requirements. The loosely coupled multiprocessor system, e.g. a torus connected one, is treated as the objective system. Two decentralized controlled load balancicg algorithms are proposed, and mathematical analyses are provided to obtain some insights of our decentralized controlled mechanisms. We also prove the proposed algorithms are steady and effective theoretically and experimentally.

An adaptive 4-state phase-frequency detector (PFD) for clock and data recovery (CDR) PLL of non return to zero (NRZ) data is presented. The PLL achieves false-lock free operation with rapid frequency-capture and wide bit-rate-capture range. The variable bit rate operation is achieved by adaptive delay control of data delay. Circuitry and overall architecture are described in detail. A z-Domain analysis is also presented.

Object detection is an essential and expensive process in many computer vision systems. Standard off-the-shelf embedded processors are hard to achieve performance-power balance for implementation of object detection applications. In this work, we explore an Application Specific Instruction set Processor (ASIP) for object detection using Histogram of Oriented Gradients (HOG) feature. Algorithm simplifications are adopted to reduce memory bandwidth requirements and mathematical complexity without losing reliability. Also, parallel histogram generation and on-the-fly Support Vector Machine (SVM) calculation architecture are employed to reduce the necessary cycle counts. The HOG algorithm on the proposed ASIP was accelerated by a factor of 63x compared to the pure software implementation. The ASIP was synthesized for a standard 90nm CMOS library, with a silicon area of 1.31mm2 and 47.8mW power consumption at a 200MHz frequency. Our object detection processor can achieve 42 frames-per-second (fps) on VGA video. The evaluation and implementation results show that the proposed ASIP is both area-efficient and power-efficient while being competitive with commercial CPUs/DSPs. Furthermore, our ASIP exhibits comparable performance even with hard-wire designs.

This paper introduces the new application specific architecture RHINE (Reconfigurable Hierarchical Image Neo-multiprocessor Engine) that is a multiprocessor system for moving picture CODEC. The array processor is known to be originally suited for data parallel processing such as image signal processing which requires vast amount of computations and has the identical instruction sequences on data. However, the moving picture CODEC algorithm suffers from the large load imbalance in the processings on multi-processors with the separated sub-images. Some load balancing techniques are indispensable in such applications for the highest speed-up. RHINE gives one of the optimal solutions for such a load balancing due to its feature of the self reconfigurable architecture. RHINE consists of Block Processing Units (BPU) hierarchically, in each of which has a common bus architecture of multiprocessors with a block memory. Processors in a BPU move to the other BPU according to the load imbalance between BPUs by switching the bus connection between BPUs. The advantage of RHINE architecture is demonstrated by showing performance simulations for real moving pictures.

Orientation field (OF) estimation is a fundamental process in fingerprint authentication systems. In this paper, a novel binary pattern based low-cost OF estimation algorithm is proposed. The new method consists of two modules. The first is block-level orientation estimation and averaging in vector space by pixel level orientation statistics. The second is orientation quantization and smoothing. In the second module, the continuous orientation is quantized into fixed orientations with sufficient resolution (interval between fixed orientations). An effective smoothing scheme on the quantized orientation space is also proposed. The proposed algorithm is capable of stably processing poor-quality fingerprint images and is validated by tests conducted on an adaptive OF matching scheme. The proposed algorithm is also implemented into a fingerprint System on Chip (SoC) to comfirm that it satisfies the strict requirements of embedded system.

It is theoretically impossible to restore the original fingerprint image from a sequence of line images captured by a line sensor. However, in this paper we propose a unique fingerprint-image-generation algorithm, which derives fingerprint images from sequences of line images captured at different swipe speeds by the line sensor. A continuous image representation, called trajectory, is used in modeling distortion of raw fingerprint images. Sequences of line images captured from the same finger are considered as sequences of points, which are sampled on the same trajectory in N-dimensional vector space. The key point here is not to reconstruct the original image, but to generate identical images from the trajectory, which are independent of the swipe speed of the finger. The method for applying the algorithm in a practical application is also presented. Experimental results on a raw fingerprint image database from a line sensor show that the generated fingerprint images are independent of swipe speed, and can achieve remarkable matching performance with a conventional minutiae matcher.

A novel binary line-pattern algorithm for embedded fingerprint authentication system is introduced in this paper. In this algorithm, each line-pattern is a one-dimension binary matrix that describes the alternation pattern of ridge and valley in fingerprint image. Two parallel lines or two cross lines in a certain scope make up related line-pattern pair. Several such line-pattern pairs at different parts of a fingerprint image can describe another intrinsic feature besides traditional minutiae feature. Experimental results showed this algorithm was not only efficient but also effective. Furthermore, a hybrid fingerprint match scheme is also introduced in this paper. It has the following features: (i) minutiae matching is firstly carried out to calculate the similarity score between the query fingerprint and the template fingerprint, and moreover, the translation and rotation parameters are obtained at the same time; (ii) line-pattern algorithm is immediately performed based on the parameters obtained after minutiae matching to get another similarity score; (iii) the final matching score is the combination of the minutiae matching score and the line-pattern matching score. Experiments were conducted on the FVC2002 database and our private database respectively. Both of the results were inspiring. In detail, at the same FAR value, the FRR of this hybrid match algorithm is to be 2-8% lower than only minutiae-based matching algorithm.

Object detection is at the heart of nearly all the computer vision systems. Standard off-the-shelf embedded processors are hard to meet the trade-offs among performance, power consumption and flexibility required by object detection applications. Therefore, this paper presents an Application Specific Instruction set Processor (ASIP) for object detection using AdaBoost-based learning algorithm with Haar-like features as weak classifiers. Algorithm optimizations are employed to reduce memory bandwidth requirements without losing reliability. In the proposed ASIP, Single Instruction Multiple Data (SIMD) architecture is adopted for fully exploiting data-level parallelism inherent to the target algorithm. With adding pipeline stages, application-specific hardware components and custom instructions, the AdaBoost algorithm is accelerated by a factor of 13.7x compared to the optimized pure software implementation. Compared with ARM946 and TMS320C64+, our ASIP shows 32x and 7x better throughput, 10x and 224x better area efficiency, 6.8x and 18.8x better power efficiency, respectively. Furthermore, compared to hard-wired designs, evaluation results show an advantage of the proposed architecture in terms of chip area efficiency while maintain a reliable performance and achieve real-time object detection at 32fps on VGA video.

In this paper, we will show some significant results of the routability analysis of bit-serial pipeline datapath designs based on Rent's rule and Donath's observation. Our results show that all of the tested bit-serial benchmarks have Rent exponent of below 0.4, indicating that the average wiring length of the circuit is expected to be independent of the circuit size. This study provides some important implications on the silicon utilization and time-area efficiency of bit-serial pipeline circuits on FPGAs and ASICs.

In this paper, a systematic method which generates the micro-architecture of Application Specific Instruction Processor (ASIP) is proposed. Different from previous works, the data path and control path are generated from the instruction sequence which is generated by translating the compiled assembly code. A graphical representation method called Register Transfer Graph (RTG) is introduced to describe the micro-operations of instruction sequence. To achieve high performance, we perform micro-operation level scheduling which dynamically assigns the micro-operations of instruction sequence to the control steps. By transforming the architecture using synthesis parameters, design space is explored more extensively. Connection cost is minimized by removing the inefficient data transfer paths.

An optimum placement of capacitors in the layout of Switched Capacitor networks is presented in this paper. The performance of integrated circuits is generally degraded by perturbations of physical parameters of each device and parasitic strays. The optimality imposed in this paper is the minimum degradation of a transfer function with respect to the distribution of capacitance values. A capacitance value per unit area fabricated on a LSI chip is assumed to be perturbed linearly with its x and y coordinates. The capacitor placement is determined so that the effects of such perturbation of capacitances to the overall transfer-characteristics are canceled. As the result, input-output transfer function will stay nominal under the linear perturbation model with arbitrary gradients.