• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.12-19
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• 2008

Detection of a number plate consists of three stages; division of a number plate, extraction of each character from the plate, recognition of the characters. Among of these three states, division stage of a number plate is the most important part and also the most time-consuming state. This paper suggests an effective region extraction method of a number plate for various images obtained from unmanned inspection systems of illegal parking violation, especially when we have to consider the diverse surrounding environments of roads. Our approaching method detects each region by investigating the characteristics in changes of brightness and intensity between the background part and character part, and the characteristics on character parts such as the sizes, heights, widths, and distance in between two characters. The method also divides a number plate into different types of the plate. This research can solve the number plate region detection failure problems caused by plate edge damages not only for Korean domestic number plates but also for new European style number plates. The method also reduces the time consumption by processing the detection in real-time, therefore, it can be used as a practical solution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2715-2720
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• 2014

Median filtering is very effective to remove impulse type noises, so it has been widely used in many signal processing applications. However, due to the time complexity of its non-linearity, median filtering is often used using a small filter window size. A lot of work has been done on devising fast median filtering algorithms, but most of them can be efficiently applied to input data with finite integer values like images. Little work has been carried out on fast 2-d median filtering algorithms that can deal with real-valued 2-d data. In this paper, a fast and simple median 2-d filter is presented, and its performance is compared with the Matlab's 2-d median filter and a heap-based 2-d median filter. The proposed algorithm is shown to be much faster than the Matlab's 2-d median filter and consistently faster than the heap-based algorithm that is much more complicated than the proposed one. Also, a more efficient median filtering scheme for 2-d real valued data with a finite range of values is presented that uses higher-bit integer 2-d median filtering with negligible quantization errors.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.149-155
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• 2021

In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.3
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• pp.166-172
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• 2022

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.194-199
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• 2022

Preprocessing for high-quality data is required for high accuracy and usability in various and complex image data-based industries. However, when a contaminated hostile example that combines noise with existing image or video data is introduced, which can pose a great risk to the company, it is necessary to restore the previous damage to ensure the company's reliability, security, and complete results. As a countermeasure for this, restoration was previously performed using Defense-GAN, but there were disadvantages such as long learning time and low quality of the restoration. In order to improve this, this paper proposes a method using adversarial examples created through FGSM according to image segmentation in addition to using the VQ-VAE model. First, the generated examples are classified as a general classifier. Next, the unsegmented data is put into the pre-trained VQ-VAE model, restored, and then classified with a classifier. Finally, the data divided into quadrants is put into the 4-split-VQ-VAE model, the reconstructed fragments are combined, and then put into the classifier. Finally, after comparing the restored results and accuracy, the performance is analyzed according to the order of combining the two models according to whether or not they are split.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.319-324
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• 2019

A depth-encoding detector module with silicon photomultipliers(SiPMs) using two layers of scintillation crystal array was designed, and the position measurement capability was verified using DETECT2000. The depth of interaction of the crystal pixels with the gamma rays was tracked through the image acquired with the combination of surface treatment of the crystal pixels and reflectors. The bottom layer was treated as a reflector except for the optically coupled surfaces, and the crystals of top layer were optically coupled each other except for the outer surfaces so that the light sharing was made easier than the bottom layer. Flood images were obtained through the combination of specular reflectors and random reflectors, grounded and polished surfaces of crystal pixels, and the positions at which layer images were generated were measured and analyzed. The images were reconstructed using the Anger algorithm, whose the SiPM signals were reduced as the 16-channels to 4-channels. In the combination of the grounded surface and all reflectors, the depth positions were discriminated into two layers, whereas it was impossible to separate the two layers in the all polished surface combinations. Therefore, using the combination of grounded surface crystal pixels and reflectors could improve the spatial resolution at the outside of the field of view by measuring the depth position in preclinical positron emission tomography.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.710-721
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• 2010

Recently, for the advancement of embedded technology about mobile device, a new kind of service, mash-up is appeared. It is service or application combining multimedia content making tool or device and web-GIS(geographic information system) service in the mobile environment. This service can be ease to use for casual user and can apply in various ways. So, It is served in web 2.0 environment actively. But, in the mashup service, because generated multimedia contents linked with web map are new type of multimedia contents which include user's migration routes in the space such as GPS coordinates. Thus, there are no protection ways for intellectual property created by GIS web-map service users and user's privacy. In this paper, we proposed a location and user information hiding scheme for GIS web-map service. This scheme embeds location and user information into a picture that is taken by camera module on the mobile phone. It is not only protecting way for user's privacy but is also tracing way against illegal photographer who is peeping person through hidden camera. And than, we also realized proposed scheme on the mobile smart phone. For minimizing margin of error about location coordinate value against contents manipulating attacks, GPS information is embedded into chrominance signal of contents considering weight of each digit about binary type of GPS coordinate value. And for tracing illegal photographer, user information such as serial number of mobile phone, phone number and photographing date is embedded into frequency spectrum of contents luminance signal. In the experimental results, we confirmed that the error of extracted information against various image processing attacks is within reliable tolerance. And after file format translation attack, we extracted embedded information from the attacked contents without no damage. Using similarity between extracted one and original templete, we also extracted whole information from damaged chrominance signal of contents by various image processing attacks.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.3
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• pp.77-85
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• 2008

This work proposes a 12b 130MS/s 108mW $1.8mm^2$ 0.18um CMOS ADC for high-quality video systems such as TFT-LCD displays and digital TVs requiring simultaneously high resolution, low power, and small size at high speed. The proposed ADC optimizes power consumption and chip area at the target resolution and sampling rate based on a three-step pipeline architecture. The input SHA with gate-bootstrapped sampling switches and a properly controlled trans-conductance ratio of two amplifier stages achieves a high gain and phase margin for 12b input accuracy at the Nyquist frequency. A signal-insensitive 3D-fully symmetric layout reduces a capacitor and device mismatch of two MDACs. The proposed supply- and temperature- insensitive current and voltage references are implemented on chip with a small number of transistors. The prototype ADC in a 0.18um 1P6M CMOS technology demonstrates a measured DNL and INL within 0.69LSB and 2.12LSB, respectively. The ADC shows a maximum SNDR of 53dB and 51dB and a maximum SFDR of 68dB and 66dB at 120MS/s and 130MS/s, respectively. The ADC with an active die area of $1.8mm^2$ consumes 108mW at 130MS/s and 1.8V.

• Journal of Biomedical Engineering Research
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• v.24 no.4
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• pp.241-246
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• 2003

To evaluate the usefulness if functional MR imaging(MRI) for the determination of language dominance system and to assess differences in the visual and auditory instrument language generation task according to activation task or activated area. Functional maps of the language area were obtained during visual and auditory instructions in word generation tasks in 6 healthy volunteer with right-handness were examined on a 1.5T scanner and the EPI BOLD technique, and three pulse sequence technique get of the true axial planes. Both task consisted of 96 phases including 6 activations and rests contents. Postprocessing were done on MRDx program by using cross correlation method. Two task compare the blain activation area surveyed of 1anguage lateralization index. To evaluated of the detection rates of Broca. Wernicke, pre-frontal lobe, Supplementary Motor Area (SMA) and pre-motor cortex areas and the differences of language lateraliaztion among two word generation task To lateralization index survey in 1anguage area on right and left in brain get to activation area pixel in brain. Compared to visual and auditory instrument task in the language areas get to the lateralization index. Two language generation task high detection rates of Broca and Wernicke areas. The visual instruction no detected in the auditory area, and auditory instruction no detected in the visual area. There was statistics significant different of them among language generation task. 1'his indicated that language area obtained image of the brain functional MR imaging usefulness in the visual and auditory task instrument.

• Investigative Magnetic Resonance Imaging
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• v.16 no.2
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• pp.136-141
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• 2012

Purpose : To investigate the pharmacologic modulation of motor task-dependent physiologic responses by antiplatelet agent, clopidogrel, during hand motor tasks in healthy subjects. Materials and Methods: Ten healthy, right-handed subjects underwent three functional magnetic resonance (fMRI) sessions: one before drug administration, one after high dose drug administration and one after reaching drug steady state. For the motor task fMRI, finger flexion-extension movements were performed. Blood oxygenation level dependent (BOLD) contrast was collected for each subject using a 3.0 T VHi (GE Healthcare, Milwaukee, USA) scanner. $T2^*$-weighted echo planar imaging was used for fMRI acquisition. The fMRI data processing and statistical analyses were carried out using SPM2. Results: Second-level analysis revealed significant increases in the extent of activation in the contralateral motor cortex including primary motor area (M1) after drug administration. The number of activated voxels in motor cortex was 173 without drug administration and the number increased to 1049 for high dose condition and 673 for steady-state condition respectively. However, there was no significant difference in the magnitude of BOLD signal change in terms of peak T value. Conclusion: The current results suggest that cerebral motor activity can be modulated by clopidogrel in healthy subjects and that fMRI is highly senstive to evidence such changes.