• Journal of Multimedia Information System
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• v.4 no.1
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• pp.9-18
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• 2017

Ubiquitous computing is a novel paradigm that is rapidly gaining in the scenario of wireless communications and telecommunications for realizing smart world. As rapid development of sensor technology, smart sensor system becomes more popular in automobile or vehicle. In this study, a new vehicle detection mechanism in real-time for blind spot area is proposed based on imaging sensors. To determine the position of other vehicles on the road is important for operation of driver assistance systems (DASs) to increase driving safety. As the result, blind spot detection of vehicles is addressed using an automobile detection algorithm for blind spots. The proposed vehicle verification utilizes the height and angle of a rear-looking vehicle mounted camera. Candidate vehicle information is extracted using adaptive shadow detection based on brightness values of an image of a vehicle area. The vehicle is verified using a training set with Haar-like features of candidate vehicles. Using these processes, moving vehicles can be detected in blind spots. The detection ratio of true vehicles was 91.1% in blind spots based on various experimental results.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.261-265
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• 2008

This work presents a simplified efficient blind detection algorithm for orthogonal space-time codes(OSTBC). First, the proposed decoder exploits a proper decomposition approach of the upper triangular matrix R, which resulted from Cholesky-factorization of the composition channel matrix, to form an easy-to-solve blind detection equation. Secondly, in order to avoid suffering from the high computational load, the proposed decoder applies a sub-optimal QR-based decoder. Computer simulation results verify that the proposed decoder allows to significantly reduce computational complexity while still satisfying the bit-error-rate(BER) performance.

• Journal of information and communication convergence engineering
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• v.4 no.4
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• pp.136-140
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• 2006

In this paper, we consider the detection of orthogonal space-time block codes (OSTBCs) without channel state information (CSI) at the receiver. Based on the conventional blind cyclic decoder, we propose an enhanced blind cyclic decoder which has higher system performance than the conventional one. Furthermore, the proposed decoder offers low complexity since it does not require the computation of singular value decomposition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.83-86
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• 2007

In the blind Maximum-likelihood (ML) detection for Orthogonal Space-Time Block Codes (OSTBC), the problem of ambiguity in determining the symbols has been a great concern. A solution to this problem is to apply semi-blind ML detection, i.e., the blind ML decoding with pilot symbols or training sequence. In order to increase the performance, the number of pilot symbols or length of training sequence should be increased. Unfortunately, this leads to a significant decrease in system spectral efficiency. This work presents an approach to resolve the aforementioned issue by introducing a new method for constructing transmitted information symbol. Thus, by transmitting information symbols drawn from different modulation constellation, the ambiguity can be easily eliminated in blind detection. Also, computer simulations are implemented to verify the performance of the proposed approach.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.5
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• pp.311-317
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• 2011

The blind spot is an area where drivers visibility does not reach. When drivers change a lane to adjacent lane, they need to give an attention because of the blind spot. If drivers try to change lane without notice of vehicle approaching in the blind spot, it causes a reason to have a car accident. This paper proposes a night-time blind spot vehicle detection using cameras. At nighttime, head-lights are used as characteristics to detect vehicles. Candidates of headlight are selected by high luminance feature and then shape filter and kalman filter are employed to remove other noisy blobs having similar luminance to head-lights. In addition, vehicle position is estimated from detected head-light, using virtual center line represented by approximated the first order linear equation. Experiments show that proposed method has relatively high detection porformance in clear weather independent to the road types, but has not sufficient performance in rainy weather because of various ground reflectors.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.150-153
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• 2008

In the blind Maximum-likelihood (ML) detection for Orthogonal Space-Time Block Codes (OSTBC), the problem of ambiguity in determining the symbols has been a great concern. A possible solution to this problem is to apply semi-blind ML detection, i.e. the blind ML decoding with pilot symbols or training sequence. In order to increase the performance, the number of pilot symbols or length of training sequence should be increased. Unfortunately, this leads to a significantly decrease in system spectral efficiency. This work presents an approach to resolve the aforementioned issue by introducing a new method for constructing transmitted information symbols, in which transmitting information symbols drawn form different modulation constellations. Therefore, the ambiguity can be easily eliminated. In addition, computer simulation is implemented to verify the performance of the proposed approach.

• KIISE Transactions on Computing Practices
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• v.23 no.7
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• pp.408-416
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• 2017

This paper proposes a real-time side-rear vehicle detection algorithm that detects vehicles quickly and accurately in blind spot areas when driving. The proposed algorithm uses a cascade classifier created by AdaBoost Learning using the MCT (modified census transformation) feature vector. Using this classifier, the smaller the detection window, the faster the processing speed of the MCT classifier, and the larger the detection window, the greater the accuracy of the MCT classifier. By considering these characteristics, the proposed algorithm uses two classifiers with different detection window sizes. The first classifier quickly generates candidates with a small detection window. The second classifier accurately verifies the generated candidates with a large detection window. Furthermore, the vehicle classifier and the wheel classifier are simultaneously used to effectively detect a vehicle entering the blind spot area, along with an adjacent vehicle in the blind spot area.

• Journal of information and communication convergence engineering
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• v.10 no.2
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• pp.175-180
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• 2012

This paper presents a blind watermark detection scheme for an additive watermark embedding model. The proposed estimation-correlation-based watermark detector first estimates the embedded watermark by exploiting non-Gaussian of the real-world audio signal and the mutual independence between the host-signal and the embedded watermark and then a correlation-based detector is used to determine the presence or the absence of the watermark. For watermark estimation, blind source separation (BSS) based on independent component analysis (ICA) is used. Low watermark-to-signal ratio (WSR) is one of the limitations of blind detection with the additive embedding model. The proposed detector uses two-stage processing to improve the WSR at the blind detector; the first stage removes the audio spectrum from the watermarked audio signal using linear predictive (LP) filtering and the second stage uses the resulting residue from the LP filtering stage to estimate the embedded watermark using BSS based on ICA. Simulation results show that the proposed detector performs significantly better than existing estimation-correlationbased detection schemes.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.64-70
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• 2017

In the commercial building such as huge enterprise building, more accurate operation of the center-controlled roller blind. We design, in this work, the target disc that its shape is nonlinearly changing and the sensor coils that are differentially arranged. The performance shows less than 1% accuracy when it is implemented in the roller blind.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.2
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• pp.198-201
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• 2014

The phase frequency detector (PFD) is one of the most important building blocks of a phase locked Loop (PLL). Due to blind-zone problem, the detection range of the PFD is low. The blind zone of a PFD directly depends upon the reset time of the PFD and the pre-charge time of the internal nodes of the PFD. Taking these two parameters into consideration, a PFD is designed to achieve a small blind zone closer to the limit imposed by process-voltage-temperature variations. In this paper an enhanced architecture is proposed for dynamic logic PFD to minimize the blind-zone problem. The techniques used are inverter sizing, transistor reordering and use of pre-charge transistors. The PFD is implemented in 180 nm technology with supply voltage of 1.8 V.