• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.298-306
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• 2013

The scale invariant feature transform (SIFT) is an effective algorithm used in object recognition, panorama stitching, and image matching. However, due to its complexity, real-time processing is difficult to achieve with current software approaches. The increasing availability of parallel computers makes parallelizing these tasks an attractive approach. This paper proposes a novel parallel approach for SIFT algorithm implementation using a block filtering technique in a Gaussian convolution process on the SIMD Pixel Processor. This implementation fully exposes the available parallelism of the SIFT algorithm process and exploits the processing and input/output capabilities of the processor, which results in a system that can perform real-time image and video compression. We apply this implementation to images and measure the effectiveness of such an approach. Experimental simulation results indicate that the proposed method is capable of real-time applications, and the result of our parallel approach is outstanding in terms of the processing performance.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.12
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• pp.1965-1974
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• 1989

This paper proposes the hidden surface removal algorithm for real time animation. The proposed algorithm can process concave polyhedrons in real time and apply to an object that penetrates others by dividing a surface into multiple surfaces. The algorithm has been implemented on IRIS workstation running Berkeley 4.2 UNIX and the program has been written in C language. The effectiveness of this algorithm is shown by flight simulation of the aircraft with several flight paths.

• Journal of IKEEE
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• v.17 no.1
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• pp.51-56
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• 2013

This thesis propose a improved matching method for implementing an ORB algorithm based multi-object recognition. SURF algorithm that is well known in the object recognition algorithms is robust in object recognition. However, there is a disadvantage for real time operation because, SURF implemention requires a lot of computation. Therefore we propose a modified ORB algorithm which shows the result of almost 70% speed improvement by improving matching part to recognize multi object on real time.

• Textile Coloration and Finishing
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• v.20 no.1
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• pp.48-56
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• 2008

A real-time inspection system has been developed by combining CCD based image processing algorithm and a standard lighting equipment. The system was tested for defective fabrics showing nozzle contact scratch marks, which are one of the frequently occurring defects. Two algorithms used were compared according to both their processing time and detection rate. First algorithm (algorithm A) was based on morphological image processing such as dilation and opening for effective treatment of defective printing areas while second one (algorithm B) mainly employs well-defined edge detection technique based on canny detector and Zermike moment. It was concluded' that although both algorithms were quite successful, algorithm B showed relatively consistent performance than algorithm A in detecting complex patterns.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.94-102
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• 2010

In recent years, embedded systems such as cellular phones, Portable Multimedia Player, intelligent appliance, automobile engine control are reshaping the way people live, work, and play. Thereby, services application to guarantee various requirements of users become increasingly sophisticated and complicated, such embedded computing platforms use real-time operating systems (RTOSs) with time determinism. These RTOSs must not only provide predictable services but must also be efficient and small in size. Kernel services should also be deterministic by specifying how long each service call will take to execute. Having this information allows the application designers to better plan their real-time application software so as not to miss the deadline of each task. In this paper, we present the complete generalized real-time scheduling algorithm using multi-dimensional methodology to determine the highest priority in the ready list with 2r levels of priorities in a constant time without additional memory overhead.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.6
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• pp.344-353
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• 2006

In this paper, we present a new algorithm which imitate real pencil strokes. The purpose of research on NPR(Non-Photorealistic Rendering) is simulating automatically manmade artistic expressions such as pen-and-ink illustrations, watercolor paintings, pencil sketches and pastel drawings with computers. Recently, there has been a great deal of research works on NPR. One of them is researching in pencil illustration methods for NPR, and a lot of researchers have investigated into the LIC(Linear Integral Convolution) techniques which would change the initial images into the output images by directional vector field images for generating effects of pencil. However, the LIC techniques can not be applied to real-time drawing tools because they are post processing techniques. This paper presents a real-time pencil strokes algorithm which is based on an observation of how pencils(from 6B to 6H) draw lines. Although this algorithm using some pencil variables and noise generation is simple, it is fast and also can draw real-time pencil strokes similar to real manmade pencil strokes in a GUI drawing tool.

• Smart Structures and Systems
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• v.18 no.5
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• pp.955-982
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• 2016

Recent studies integrating vibration control and structural health monitoring (SHM) use control devices and control algorithms to enable system identification and damage detection. In this study real-time SHM is used to enhance structural vibration control and reduce damage. A newly proposed control algorithm, including integrated real-time SHM and semi-active control strategy, is presented to mitigate both damage and seismic response of the main structure under strong seismic ground motion. The semi-active independently variable stiffness (SAIVS) device is used as semi-active control device in this investigation. The proper stiffness of SAIVS device is obtained using a new developed semi-active control algorithm based on real-time damage tracking of structure by damage detection algorithm based on identified system Markov parameters (DDA/ISMP) method. A three bay five story steel braced frame structure, which is equipped with one SAIVS device at each story, is employed to illustrate the efficiency of the proposed algorithm. The obtained results show that the proposed control algorithm could significantly decrease damage in most parts of the structure. Also, the dynamic response of the structure is effectively reduced by using the proposed control algorithm during four strong earthquakes. In comparison to passive on and off cases, the results demonstrate that the performance of the proposed control algorithm in decreasing both damage and dynamic responses of structure is significantly enhanced than the passive cases. Furthermore, from the energy consumption point of view the maximum and the cumulative control force in the proposed control algorithm is less than the passive-on case, considerably.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11B
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• pp.991-1000
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• 2004

This paper presents an application layer multicast tree constructing algorithm to minimize the average time delay from the sender to end-systems for the effective real-time media delivery. Simultaneously, the proposed algorithm takes into account the computing power and the network condition of each end-system as a control variable and thus avoids the undesirable case that loads are concentrated to only several end-systems. The multicast tree is constructed by clustering technique and modified Dijkstra's algorithm in two steps, i.e. tree among proxy-senders and tree in each cluster. By the experimental results, we show that the proposed algorithm can provide an effective solution.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.4 s.95
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• pp.427-437
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• 2005

In this paper, the perceived audio level metering algorithm of digital audio sound to be able to operate in real-time is proposed. Through analyzing a conventional recommendation ITU-RBS1387-I for objective audio quality analysis, FFT-based loudness metering algorithm is implemented and the real-time method of that algorithm was advised and proved. The proposed method is based on look-up table. In order to prove the proved method, using 23 pure tones and 30 preselected digital audio samples, its performance and operation time is evaluated. Its performance, compared with an original algorithm's, have a good figure of less than $2\;\%$ error even if look-up table related with spectral spreading have large level resolution of $10\;\cal{dB}$. The proposed algorithm take only 1/21 of original algorithm's measuring time. Also, in the proposed algorithm auditory pitch group energy calculation take 1/450 of original algorithm's and excitation calculation take 1/3.57. In conclusion, the proposed algorithm is expected to be implemented into DSP-based real-time loudness meter.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.463-481
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• 2020

Cutter suction dredgers (CSDs) are widely used in various dredging constructions such as channel excavation, wharf construction, and reef construction. During a CSD construction, the main operation is to control the swing speed of cutter to keep the slurry concentration in a proper range. However, the slurry concentration cannot be monitored in real-time, i.e., there is a "time-lag effect" in the log of slurry concentration, making it difficult for operators to make the optimal decision on controlling. Concerning this issue, a solution scheme that using real-time monitored indicators to predict current slurry concentration is proposed in this research. The characteristics of the CSD monitoring data are first studied, and a set of preprocessing methods are presented. Then we put forward the concept of "index class" to select the important indices. Finally, an ensemble learning algorithm is set up to fit the relationship between the slurry concentration and the indices of the index classes. In the experiment, log data over seven days of a practical dredging construction is collected. For comparison, the Deep Neural Network (DNN), Long Short Time Memory (LSTM), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and the Bayesian Ridge algorithm are tried. The results show that our method has the best performance with an R² of 0.886 and a mean square error (MSE) of 5.538. This research provides an effective way for real-time predicting the slurry concentration of CSDs and can help to improve the stationarity and production efficiency of dredging construction.