• Journal of Sensor Science and Technology
• /
• v.12 no.3
• /
• pp.128-138
• /
• 2003

In this paper, we proposed the algorithm for locating destination address block (DAB) from automatic system to classify packages. For locating DAB, because the size of obtained images is are very large, we select the region of interesting (ROI) to reduce time carrying into algorithm. After selecting the ROI, proposed algorithm is carried out within the ROI. We extract the outline of the handwriting part of the DAB and the rest components within the obtained ROI using thresholding. We carry out labeling to extract each connected component for extracted outline and the rest components. We extract the outline of the handwriting part of the DAB using the geometrical characteristic of the outline of the handwriting part of the DAB among many connected components. The last, we extract the locating DAB using the outline of the handwriting part of the DAB.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.4 no.1
• /
• pp.35-41
• /
• 2009

The H.264/SVC enables network-adaptive video transmission to smart device which uses wireless network. But, quality scalability of H.264/SVC does not consider personal subjective image quality. In addition, its network efficiency also does not optimized because it uses MGS(Medium Grained Scalability) and CGS(Coarse Grained Scalability). Thus, this paper proposed a new scalable ROI algorithm for not only subjective image quality improvement but also network adaptation. To experiment our proposed a scheme, we added designed algorithm to JSVM(Joint Scalable Video Model) open source video codec of H.264/SVC. Experiment was performed according to the pre-defined scenario for simulating various network conditions. Finally, experimental result showed our proposed scalable ROI scheme. It is better than traditional non-selective scheme in subjective video quality.

• Journal of radiological science and technology
• /
• v.41 no.5
• /
• pp.457-462
• /
• 2018

The purpose of this study was to compare image quality of indirect digital radiography (IDR) system using the International Electro-technical Commission standard (IEC 62220-1), and to suggest the analysis of noise power spectrum (NPS) which were applied to IEC 62220-1 in medical imaging. In this study, Pixium 4600 (Trixell, France) which is indirect flat panel detector (FPD) was used. The size of image receptor (IR) is $7{\times}17$ inch (matrix $3001{\times}3001$) which performed 14bit processing and pixel pitch is $143{\mu}m$. In IEC standard, NPS evaluation were applied to RQA3, RQA5, RQA7 and RQA9. Because of different radiation quality, each region of interesting (ROI) were compared. The results of NPS indicated up to $3.5mm^{-1}$ including low Nyquist frequency. RQA5 indicated the lowest NPS and the others indicated higher NPS results relatively. NPS result of ROI a38 was higher than ROI a92 and this result indicated that there are more noise in left (cathode) than right (anode). This study were to evaluate NPS by using different radiation quality and setting the each ROI, and to suggest the quantitative methods of measuring NPS.

• Journal of IKEEE
• /
• v.23 no.1
• /
• pp.235-241
• /
• 2019

In this paper, we propose a new algorithm to detect rear-approaching vehicle using the frame similarity of ROI(Region of Interest) based on deep learning algorithm for use in agricultural machinery systems. Since the vehicle detection system for agricultural machinery needs to detect only a vehicle approaching from the rear. we use Faster R-CNN model that shows excellent accuracy rate in deep learning for vehicle detection. And we proposed an algorithm that uses the frame similarity for ROI using constrained conditions. Experimental results show that the proposed method has a detection rate of 99.9% and reduced the false positive values.

• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.5
• /
• pp.596-600
• /
• 2010

This paper proposes hough transform-based semi-automatic vertex detection algorithm for object modeling on a mobile phone supporting touch-screens. The proposed algorithm shows fast processing time by searching the limited range of parameters for computing hough transform with a small range of ROI image. Moreover, the proposed algorithm removes bad candidates among the detected lines by selecting the two closest candidate lines from the position of user's input. After that, it accurately detects an interesting vertex without additionally required interactions by detecting an intersection point of the two lines. As a result, we believe that the proposed algorithm shows a 1.4 pixel distance error on average as a vertex detection accuracy under such conditions as a 5.7 pixel distance error on average as an inaccurate input.

• Journal of Veterinary Clinics
• /
• v.25 no.3
• /
• pp.176-181
• /
• 2008

Fluid accumulation within the tympanic bulla is an important diagnostic indicator of canine otitis media although its identification can be a challenge using currently available imaging techniques. The purpose of this study was to compare radiography, computed tomography (CT) and magnetic resonance imaging (MRI) in the identification of fluid accumulation within canine tympanic bulla. Unilateral tympanic bulla in 10 beagles were experimentally filled with blood or saline. Quantitative analysis of CT images were obtained by using Hounsfield unit (HU). MR signal intensity was obtained by using region of interesting (ROI) and compared with those of gray matter. On the CT image, the presence of blood or saline produced a fluid opacity occupying the tympanic bulla. On the MR image, the appearance of blood in the tympanic bulla was isointense in T1-weighted images and hyperintense in T2-weighted images. However, the appearance of saline in the tympanic bulla was hypointense in T1-weighted images and hyperintense in T2-weighted images. This study suggest that CT and MR imaging are useful methods for detection and differentiation of fluid in canine tympanic bulla.

• Journal of the Korea Society of Computer and Information
• /
• v.17 no.1
• /
• pp.71-80
• /
• 2012

This paper proposes vehicle detection and tracking algorithm using a CCD camera. The proposed algorithm uses Haar-like wavelet edge detector to detect features of vehicle and estimates vehicle's location using calibration information of an image. After that, extract accumulated vehicle information in continuous k images to improve reliability. Finally, obtained vehicle region becomes a template image to find same object in the next continuous image using SURF(Speeded Up Robust Features). The template image is updated in the every frame. In order to reduce SURF processing time, ROI(Region of Interesting) region is limited on expended area of detected vehicle location in the previous frame image. This algorithm repeats detection and tracking progress until no corresponding points are found. The experimental result shows efficiency of proposed algorithm using images obtained on the road.