• Journal of Information Technology Services
• /
• v.10 no.4
• /
• pp.243-258
• /
• 2011

With increasing interest in ubiquitous computing technology, an infrastructure for the short-distance wireless communication has been extended socially, bringing spotlight to the security system using the image or location. In case of existing security system, there have been issues such as the occurrences of blind spots, difficulty in recognizing multiple objects and storing of the unspecified objects. In order to solve this issue, zone-based location-estimation search system for the image have been suggested as an alternative based on the real-time location determination technology combined with image. This paper intends to suggest the search service for the image zone-based location-estimation. For this, it proposed the location determination algorism using IEEE 802.15.4/ZigBee's RSSI and for real-time image service, the RTP/RTCP protocol was applied. In order to combine the location and image, at the event of the entry of the specified target, the record of the time for image and the time of occurrence of the event on a global time standard, it has devised a time stamp, applying XML based meta data formation method based on the media's feature data based in connection with the location based data for the events of the object. Using the proposed meta data, the service mode which can search for the image from the point in time when the entry of the specified target was proposed.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.1 no.2
• /
• pp.27-31
• /
• 2000

Thermal imaging system is implemented for the measurement and the analysis of the thermal distribution of the target objects. The main Part of the system is thermal camera in which a focal plane array typed sensor is introduced The sensor detects mid-range infrared spectrum or target objects and then it output generic video signal which should be processed to form a thermal image frame. A digital signal processor(DSP) in the system inputs analog to digital converted data. performs algorithms to improve the thermal images and then outputs the corrected frame data to frame buffers for NTSC encoding and for digital outputs.. To enhance the quality of the thermal images, two point correction method is applied. Figures indicate that the corrected thermal images are much improved.

• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.496-500
• /
• 1998

Not merely running at the designated constant speed as the classical cruise control, the adaptive cruise control (ACC) maintains safe headway distance when the front is blocked by other vehicles. One of the most essential part of ACC System is the range sensor which can measure the position and speed of all objects in front continuously, ignore all irrelevant objects, distinguish vehicles in different lanes and lock on to the closest vehicle in the same lane. In this paper, the hierarchical object recognition algorithm (HORA) is proposed to process raw scanning laser data and acquire valid distance to target vehicle. HORA contains two principal concepts. First, the concept of life quantifies the reliability of range data to filter off the spurious detection and preserve the missing target position. Second, the concept of conformation checks the mobility of each obstacle and tracks the position shift. To estimate and predict the vehicle position Kalman filter is used. Repeatedly updated covariance matrix determines the bound of valid data. The algorithm is emulated on computer and tested on-line with our ACC vehicle.

• Journal of Korea Multimedia Society
• /
• v.24 no.3
• /
• pp.416-422
• /
• 2021

Due to the large differences in human activity within classes, the large similarity between classes, and the problems of visual angle and occlusion, it is difficult to extract features manually, and the detection rate of human behavior is low. In order to better solve these problems, an improved Faster R-CNN-based detection algorithm is proposed in this paper. It achieves multi-object recognition and localization through a second-order detection network, and replaces the original feature extraction module with Dense-Net, which can fuse multi-level feature information, increase network depth and avoid disappearance of network gradients. Meanwhile, the proposal merging strategy is improved with Soft-NMS, where an attenuation function is designed to replace the conventional NMS algorithm, thereby avoiding missed detection of adjacent or overlapping objects, and enhancing the network detection accuracy under multiple objects. During the experiment, the improved Faster R-CNN method in this article has 84.7% target detection result, which is improved compared to other methods, which proves that the target recognition method has significant advantages and potential.

• Transactions on Control, Automation and Systems Engineering
• /
• v.4 no.1
• /
• pp.92-99
• /
• 2002

To obtain visual information of a target object, a camera should be placed within the visibility region. As the visibility region is dependent on the relative position of the target object and the surrounding object, the position change of the surrounding object during a task requires recalculation of the visibility region. For a fast computation of the visibility region so as to modify the camera position to be located within the visibility region, we propose a spherical projection method. After being projected onto the sphere the visibility region is represented in $\theta$-$\psi$ spaces of the spherical coordinates. The reduction of calculation space enables a fast modification of the camera location according to the motion of the surrounding objects so that the continuous observation of the target object during the task is possible.

• Journal of electromagnetic engineering and science
• /
• v.10 no.3
• /
• pp.166-170
• /
• 2010

To numerically calculate electromagnetic scattering from the electrical-large three-dimensional(3D) objects, the high-frequency approaches have been usually applied, but the accuracy and feasibility of these geometrical and physical optics(GO-PO) approaches, to some extent, are remained to be improved. In this paper, a new framework is developed for calculation of the near-field scattering field of an electrical-large 3D target by using a multilevel fast multipole algorithm(MLFMA) and generation of radar images by using a fast back-projection(FBP) algorithm. The MPI(Message Passing Interface) parallel computing is carried out to multiply the calculation efficiency greatly. Finally, a simple example of perfectly electrical conducting(PEC) patch and a canonical case of Fighting Falcon F-16 are presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.1128-1131
• /
• 1996

The collision-free path planning presented here uses linear parametric curve with one intermediate connection point between start and target points. The algorithm, in which connection point is organized in elliptic chord.(.theta., .delta.), maps objects in Euclidean Space into images in CPS through intersection check between path and obstacles a process defined as GM. Elliptic locus has special property that the total distance between focus points through a point on ellipse is the same regardless of .theta.. Hence by locating the start and target points to focus points of ellipse, and organizing connection point in elliptic coordinate, the .delta.-axis of CPS represents length of path. The GM of EWS requires calculation of interference in circumferential direction only. The procedures for GM is developed which include categorization of obstacles to reduce calculation amount. Simulations of GM of EWS, on a PC with Pentium/90MHz, is carried out to measure performance of algorithm and the results are reported on a table. The simulations are done for number of cases with different number of obstacles and location of start/target points.

• Journal of Korea Multimedia Society
• /
• v.25 no.2
• /
• pp.247-256
• /
• 2022

Visual tracking of selected target objects is fundamental challenging problems in computer vision. Object tracking localize the region of target object with bounding box in the video. We propose a Siam-FPN based custom fully CNN to solve visual tracking problems by regressing the target area in an end-to-end manner. A method of preserving the feature information flow using a feature map connection structure was applied. In this way, information is preserved and emphasized across the network. To regress object region and to classify object, the region proposal network was connected with the Siamese network. The performance of the tracking algorithm was evaluated using the OTB-100 dataset. Success Plot and Precision Plot were used as evaluation matrix. As a result of the experiment, 0.621 in Success Plot and 0.838 in Precision Plot were achieved.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.11
• /
• pp.2321-2326
• /
• 2011

Cervical vertebrae are a complex structure and an important part of human body connecting the head and the trunk. In this paper, we propose a method to extract sternocleidomastoid muscle from ultrasonography images of cervical vertabrae automatically. In our method, Region of Interests(ROI) is extracted first from an ultrasonography image after removing unnecessary auxiliary information such as metrics. Then we apply Ends-in search stretching algorithm in order to enhance the contrast of brightness. Average binarization is then applied to those pixels which its brightness is sufficiently large. The noise part is removed by image processing algorithms. After extracting fascia encloses sternocleidomastoid muscle, target muscle object is extracted using the location information of fascia according to the number of objects in the fascia. When only one object is to be extracted, we search downward first to extract the target muscle area and then search from right to left to extract the area and merge them. If there are two target objects, we extract first from the upper-bound of higher object to the lower-bound of lower object and then remove the fascia of the target object area. Smearing technique is used to restore possible loss of the fat area in the process. The thickness of sternocleidomastoid muscle is then calculated as the maximum thickness of those extracted objects. In this experiment with 30 real world ultrasonography images, the proposed method verified its efficacy and accuracy by health professionals.

• The Journal of Korean Society for Radiation Therapy
• /
• v.12 no.1
• /
• pp.20-25
• /
• 2000

The accuracy of the target localization was evaluated by conventional and spiral CT in stereotactic radiosurgerv. Conventional and spiral CT images were obtained with geometrical phantom, which was designed to produce exact three-dimensional coordinates of several objects within 0.1mm error range. Geometrical phantom was attached by BRW headframe, intermediate head ring, and CT localizer. Twentv-seven slices of conventional CT image were scanned at 3 mm slice thickness. Spiral CT images were scanned at 3 mm slice thickness from the pitch value 1 to 3, and twenty-seven slices of image were obtained per each the pitch value. These CT images were transferred to a treatment planning system(X-knife, Radionics) by ethernet, Three-dimensional coordinates of these images measured from the treatment planning system were compared to known values of geometrical phantom. The mean localization error of the target localization of conventional CT was 1.4mm. In case of spiral CT, the error of the target localization was within 1.6mm from the pitch value 1 to 1.3, but was more than 30mm above the pitch value 1.5. In conclusion, as the localization error of spiral CT was increased in high pitch value compared to conventional CT, the application of spiral CT will be with caution in stereotactic radiosurgery.