A Novel Architecture of Vision Chip for Fast Traffic Lane Detection and FPGA Implementation

This paper presents a novel architecture of vision chip for fast traffic lane detection (FTLD). The architecture consists of a 32*32 SIMD processing element (PE) array processor and a dual-core RISC processor. The PE array processor performs low-level pixel-parallel image processing at high speed and outputs image features for high-level image processing without I/O bottleneck. The dual-core processor carries out high-level image processing. A parallel fast lane detection algorithm for this architecture is developed. The FPGA system with a CMOS image sensor is used to implement the architecture. Experiment results show that the system can perform the fast traffic lane detection at 50fps rate. It is much faster than previous works and has good robustness that can operate in various intensity of light. The novel architecture of vision chip is able to meet the demand of real-time lane departure warning system.

A Smart Frequency Presetting Technique for Fast Lock-in LC-PLL Frequency Synthesizer

This paper proposes a smart frequency presetting technique for fast lock-in LC-PLL frequency synthesizer. The technique accurately presets the frequency of VCO with small initial frequency error and greatly reduces the lock-in time. It can automatically compensate preset frequency variation with process and temperature. A 2.4GHz synthesizer with 1MHz reference input was implemented in 0.35 mu m CMOS process. The chip core area is 0.4mm(2). Output frequency of VCO ranges from 2390 to 2600MHz. The measured results show that the typical lock-in time is 3 mu s. The phase noise is -112dBc/Hz at 600KHz offset from center frequency. The test chip consumes current of 22mA that includes the consumption of the I/O buffers.

Fast Discrimination of Commerical Corn Varieties Based on Near Infrared Spectra

The existing methods for the discrimination of varieties of commodity corn seed are unable to process batch data and speed up identification, and very time consuming and costly. The present paper developed a new approach to the fast discrimination of varieties of commodity corn by means of near infrared spectral data. Firstly, the experiment obtained spectral data of 37 varieties of commodity corn seed with the Fourier transform near infrared spectrometer in the wavenurnber range from 4 000 to 12 000 cm (1). Secondly, the original data were pretreated using statistics method of normalization in order to eliminate noise and improve the efficiency of models. Thirdly, a new way based on sample standard deviation was used to select the characteristic spectral regions, and it can search very different wavenumbers among all wavenumbers and reduce the amount of data in part. Fourthly, principal component analysis (PCA) was used to compress spectral data into several variables, and the cumulate reliabilities of the first ten components were more than 99.98%. Finally, according to the first ten components, recognition models were established based on BPR. For every 25 samples in each variety, 15 samples were randomly selected as the training set. The remaining 10 samples of the same variety were used as the first testing set, and all the 900 samples of the other varieties were used as the second testing set. Calculation results showed that the average correctness recognition rate of the 37 varieties of corn seed was 94.3%. Testing results indicate that the discrimination method had higher precision than the discrimination of various kinds of commodity corn seed. In short, it is feasible to discriminate various varieties of commodity corn seed based on near infrared spectroscopy and BPR.

ZnO thin film photoconductive ultraviolet detector with fast photoresponse

C-axis preferred oriented ZnO thin films were prepared on quartz substrates by RF sputtering. Photoconductive ultraviolet detector with planar interdigital electrodes was fabricated on ZnO thin film by the lift off technique. Linear I-V characteristic was observed under dark or 365 nm UV light illumination and has obvious difference. The photoresponsivity of 365 nm at 5 V bias is 18 A/W. The response time measure set mainly contains KrF excimer laser with the pulse width of 30 ns and the oscillograph with the bandwidth of 200 MHz. The result shows fast photoresponse with a rise time of 100 ns and fall time of 1.5 mu s. (c) 2005 Elsevier B.V. All rights reserved.

Fast and effective analysis methods for fiber Raman amplifiers

A series of new single-step methods and their corresponding algorithms with automatic step size adjustment for model equations of fiber Raman amplifiers are proposed and compared in this paper. On the basis of the Newton-Raphson method, multiple shooting algorithms for the two-point boundary value problems involved in solving Raman amplifier propagation equations are constructed. A verified example shows that, compared with the traditional Runge-Kutta methods, the proposed methods can increase the accuracy by more than two orders of magnitude under the same conditions. The simulations for Raman amplifier propagation equations demonstrate that our methods can increase the computing speed by more than 5 times, extend the step size significantly, and improve the stability in comparison with the Dormand-Prince method. The numerical results show that the combination of the multiple shooting algorithms and the proposed methods has the capacity to rapidly and effectively solve the model equations of multipump Raman amplifiers under various conditions such as co-, counter- and bi-directionally pumped schemes, as well as dual-order pumped schemes.