• International Journal of Control, Automation, and Systems
• /
• v.6 no.3
• /
• pp.413-423
• /
• 2008

The template matching method is used as a simple method to track objects or patterns that we want to search for in the input image data from image sensors. It recognizes a segment with the highest correlation as a target. The concept of this method is similar to that of SNF (Strongest Neighbor Filter) that regards the measurement with the highest signal intensity as target-originated among other measurements. The SNF assumes that the strongest neighbor (SN) measurement in the validation gate originates from the target of interest and the SNF utilizes the SN in the update step of a standard Kalman filter (SKF). The SNF is widely used along with the nearest neighbor filter (NNF), due to computational simplicity in spite of its inconsistency of handling the SN as if it is the true target. Probabilistic Strongest Neighbor Filter for m validated measurements (PSNF-m) accounts for the probability that the SN in the validation gate originates from the target while the SNF assumes at any time that the SN measurement is target-originated. It is known that the PSNF-m is superior to the SNF in performance at a cost of increased computational load. In this paper, we suggest an image tracking algorithm that combines the template matching and the PSNF-m to estimate the states of a tracked target. Computer simulation results are included to demonstrate the performance of the proposed algorithm in comparison with other algorithms.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.2
• /
• pp.95-104
• /
• 2012

In this paper, an estimation of person height and 3D location of a moving person by using the pan/tilt-embedded stereo tracking system is suggested and implemented. In the proposed system, face coordinates of a target person is detected from the sequential input stereo image pairs by using the YCbCr color model and phase-type correlation methods and then, using this data as well as the geometric information of the stereo tracking system, distance to the target from the stereo camera and 3-dimensional location information of a target person are extracted. Basing on these extracted data the pan/tilt system embedded in the stereo camera is controlled to adaptively track a moving person and as a result, moving trajectory of a target person can be obtained. From some experiments using 780 frames of the sequential stereo image pairs, it is analyzed that standard deviation of the position displacement of the target in the horizontal and vertical directions after tracking is kept to be very low value of 1.5, 0.42 for 780 frames on average, and error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 0.5% on average. These good experimental results suggest a possibility of implementation of a new stereo target tracking system having a high degree of accuracy and a very fast response time with this proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.7
• /
• pp.814-820
• /
• 1999

We propose a target identification algorithm for visual tracking. Target identification is realized by finding out corresponding line segments to the hypothesized model segments of the target. The key idea is the combination of the Mahalanobis distance with the geometrical relationship between model segments and extracted line segments.

• Korean Journal of Remote Sensing
• /
• v.31 no.5
• /
• pp.433-440
• /
• 2015

In stochastic hyperspectral target detection algorithms, the target signal components may be included in the background characterization if targets are not rare in the image, causing target leakage. In this paper, the effect of target leakage is analysed and an improved hyperspectral target detection method is proposed by excluding the pixels which have similar reflectance spectrum with the target in the process of background characterization. Experimental results using the AISA airborne hyperspectral data and simulated data with artificial targets show that the proposed method can dramatically improve the target detection performance of matched filter and adaptive cosine estimator. More studies on the various metrics for measuring spectral similarity and adaptive method to decide the appropriate amount of exclusion are expected to increase the performance and usability of this method.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.5C
• /
• pp.355-364
• /
• 2012

Target processing mechanisms are necessary to collect target information, real-time data fusion, and tactical environment recognition for cooperative engagement ability. Among these mechanisms, the target tracking starts from predicting state of speed, acceleration, and location by using sensors' measurements. However, it can be a problem to give the reliability because the measurements have a certain uncertainty. Thus, a technique which uses multiple sensors is needed to detect the target and increase the reliability. Also, data fusion technique is necessary to process the data which is provided from heterogeneous sensors for target tracking. In this paper, a target tracking algorithm is proposed based on probabilistic data association(PDA) by fusing radar and ESM sensor measurements. The radar sensor's azimuth and range measurements and the ESM sensor's bearing-only measurement are associated by the measurement fusion method. After gating associated measurements, state estimation of the target is performed by PDA filter. The simulation results show that the proposed algorithm provides improved estimation under linear and circular target motions.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.4
• /
• pp.304-309
• /
• 2013

This paper proposes a intelligent approach on range decision of figure of merit. Unknown range of the underwater target and the non-fixed signal excess make the uncertainty for the tracking process. Using the input data of signal excess related to the range, we establish the rule of the fuzzy set and the original data acquired by sonar can be transformed to the fuzzified data set. To reduce the error arisen from the unexpected data, we use the new data transformed in fuzzy set. The piecewise relations of the min value, max one, and the mean one are calculated. The three values are used for the expected range of the underwater target. By analysing the fluctuation of the data, we can expect the target's position and the characteristics of the maneuvering. The examples are presented to show the performance and the effectiveness of the proposed method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.27 no.6
• /
• pp.545-556
• /
• 2016

JPDAF is a method of updating target's state estimation by using posterior probability that measurements are originated from existing target in multi-target tracking. In this paper, we propose a multi-target tracking algorithm for falling cluster bombs separated from a mother bomb based on JPDAS method which is obtained by applying fixed-interval smoothing technique to JPDAF. The performance of JPDAF and JPDAS multi-target tracking algorithm is compared by observing the average of the difference between targets' state estimations obtained from 100 independent executions of two algorithms and targets' true states. Based on this, results of simulations for a radar tracking problem that show proposed JPDAS has better tracking performance than JPDAF is presented.

• Journal of Biomedical Engineering Research
• /
• v.10 no.3
• /
• pp.223-228
• /
• 1989

In this paper, the computerized interpretation of the analytical chemical data, especially GC/MS data, was performed for the purpose of prescreening of the target compounds. First, the data from the analytical instrument was analyzed to get the information about the retention time of the ISTD and the time inteval between the records. Second, the identification of the characteristic ion peaks was performed by calculating the ratio of the heights and the relative slope sensitivity of the characteristic mass abundance.

• Progress in Medical Physics
• /
• v.28 no.4
• /
• pp.181-189
• /
• 2017

The conventional delivery quality assurance (DQA) process for RapidArc (Varian Medical Systems, Palo Alto, USA), has the limitation that it measures and analyzes the dose in a phantom material and cannot analyze the dosimetric changes under the motional organ condition. In this study, a DQA method was designed to overcome the limitations of the conventional DQA process for internal target volume (ITV) based RapidArc. The dynamic DQA measurement device was designed with a moving phantom that can simulate variable target motions. The dose distribution in the real volume of the target and organ-at-risk (OAR)s were reconstructed using 3DVH with the ArcCHECK (SunNuclear, Melbourne, USA) measurement data under the dynamic condition. A total of 10 ITV-based RapidArc plans for liver-cancer patients were analyzed with the designed dynamic DQA process. The average pass rate of gamma evaluation was $81.55{\pm}9.48%$ when the DQA dose was measured in the respiratory moving condition of the patient. Appropriate method was applied to correct the effect of moving phantom structures in the dose calculation, and DVH data of the real volume of target and OARs were created with the recalculated dose by the 3DVH program. We confirmed the valid dose coverage of a real target volume in the ITV-based RapidArc. The variable difference of the DVH of the OARs showed that dose variation can occur differently according to the location, shape, size and motion range of the target. The DQA process devised in this study can effectively evaluate the DVH of the real volume of the target and OARs in a respiratory moving condition in addition to the simple verification of the accuracy of the treatment machine. This can be helpful to predict the prognosis of treatment by the accurate dose analysis in the real target and OARs.

• 제어로봇시스템학회:학술대회논문집
• /
• 1990.10a
• /
• pp.789-793
• /
• 1990

Preprocessing technique of the measurement bearing data is presented to improve the tar-get estimation accuracy for the bearing-only target notion analysis (TMA). Computer simulation is performed to compare with respect to the extended Kalman filter. By computer simulation, the target filter estimator with preprocessing Is both stable and robust to the measurement bearing noise.