• Journal of Biomedical Engineering Research
• /
• v.10 no.3
• /
• pp.293-302
• /
• 1989

A Dual Sensor Wiener Filter technique was used to improve the image quality of the scanning type digital radiographic system (resolution and SNR). In this method, two images were acquried simultaneously using two sensors with high and low resolution and SNR values. Using the cross Power spectrum between dual sensor outputs of the same chest radiographic image. we design a new type of Wiener Filter and implement it with fast algorithm. We compared the performance of this new dual sensor filter with conventional single sensor filters (Wiener Filter and Parametric Projec- tion Filter) . In simulation studies, it is shown that this new method has SNR improvement of 1-3 dB better than conventional filters.

• Proceedings of the KIEE Conference
• /
• 1987.07b
• /
• pp.1383-1386
• /
• 1987

This paper concerns, the method for velocity of dynamic Image on two dimensional sequence Image which can be obtained from two sample lines on the street. The velocity of a single moving object Is measured by the number of total frame which Is required when an automobile passes over the second sample line through the first sample line. The measured results show that the velocity error Is less than 5% comparing with the value measured by X-band speed gun.

• International Journal of Internet, Broadcasting and Communication
• /
• v.10 no.4
• /
• pp.50-64
• /
• 2018

This paper describes a visual object detection approach utilizing ensemble based machine learning. Object detection methods employing 1D features have the benefit of fast calculation speed. However, for real image with complex background, detection accuracy and performance are degraded. In this paper, we propose an ensemble learning algorithm that combines a 1D feature classifier and 2D DNF (Disjunctive Normal Form) classifier to improve the object detection performance in a single input image. Also, to improve the computing efficiency and accuracy, we propose a feature selecting method to reduce the computing time and ensemble algorithm by combining the 1D features and 2D DNF features. In the verification experiments, we selected the Haar-like feature as the 1D image descriptor, and demonstrated the performance of the algorithm on a few datasets such as face and vehicle.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.855-856
• /
• 2008

In this paper, we studied the performance evaluation of a vehicular rear-view camera through quantifying the image quality based on several objective criteria from the ISO (International Organization for Standardization). In addition, various experimental environments are defined considering the conditions under which a rear-view camera may need to operate. The process for evaluating the performance of a rear-view camera is composed of five objective criteria: noise test, resolution test, OECF (opto-electronic conversion function) test, color characterization test, and pincushion and barrel distortion tests. The proposed image quality quantification method then expresses the results of each test as a single value, allowing easy evaluation.

• The Journal of the Acoustical Society of Korea
• /
• v.18 no.8
• /
• pp.68-74
• /
• 1999

To investigate the relationship between voice and the image created by the voice, a perception experiment was undertaken in which voices of 8 males and 8 females reading a fairy tale were recorded and presented to 100 subjects along with the speakers' pictures. Two kinds of pictures were taken: one, a whole-body picture, and the other, a face-only close-up picture. Subjects were asked to match each voice with its owner. The results showed that out of 8, more than 4 were matched correctly. And the correct rate was higher when the voices were matched against the whole-body pictures than against the face-only pictures. In addition, it was noted that far more people picked a single voice as the most 'favorite' one than they picked one picture as the most 'favorite' image.

• Journal of Advanced Marine Engineering and Technology
• /
• v.28 no.4
• /
• pp.611-617
• /
• 2004

Pixel classification is one of basic image processing issues. The general characteristics of the pixels belonging to various classes are discussed and the radical principles of pixel classification are given. At the same time. a pixel classification scheme based on image direction measure is proposed. As a typical application instance of pixel classification, an adaptive multi-level median filter is presented. An image can be classified into two types of areas by using the direction information measure, that is. smooth area and edge area. Single direction multi-level median filter is used in smooth area. and multi-direction multi-level median filter is taken in the other type of area. What's more. an adaptive mechanism is proposed to adjust the type of the filters and the size of filter window. As a result. we get a better trade-off between preserving details and noise filtering.

• International Journal of Contents
• /
• v.8 no.1
• /
• pp.16-22
• /
• 2012

In this paper we propose a method for verifying video in a video telephony system implemented in DM6446 DaVinci Processor. Each frame is categorized either error free frame or error frame depending on the predefined criteria. Human face is chosen as a basic means for authenticating the video frame. Skin color based algorithm is implemented for detecting the face in the video frame. The video frame is classified as error free frame if there is single face object with clear view of facial features (eyes, nose, mouth etc.) and the background of the image frame is not different then the predefined background, otherwise it will be classified as error frame. We also implemented the image histogram based NCC (Normalized Cross Correlation) comparison for video verification to speed up the system. The experimental result shows that the system is able to classify frames with 90.83% of accuracy.

• Korean Journal of Computational Design and Engineering
• /
• v.20 no.4
• /
• pp.357-366
• /
• 2015

We review recent research results on coupled line cameras (CLC) as a new geometric tool to reconstruct a scene quadrilateral from image quadrilaterals. Coupled line cameras were first developed as a camera calibration tool based on geometric insight on the perspective projection of a scene rectangle to an image plane. Since CLC comprehensively describes the relevant projective structure in a single image with a set of simple algebraic equations, it is also useful as a geometric reconstruction tool, which is an important topic in 3D computer vision. In this paper we first introduce fundamentals of CLC with reals examples. Then, we cover the related works to optimize the initial solution, to extend for the general quadrilaterals, and to apply for cuboidal reconstruction.

• Maxillofacial Plastic and Reconstructive Surgery
• /
• v.37
• /
• pp.43.1-43.5
• /
• 2015

Image-guided surgery potentially enhances intraoperative safety and outcomes in a variety of craniomaxillofacial procedures. We explore the efficiency of one intraoperative navigation system in a single complex craniofacial case, review the initial and recurring costs, and estimate the added cost (e.g., additional setup time, registration). We discuss the potential challenges and benefits of utilizing image-guided surgery in our specific case and its benefits in terms of educational and teaching purposes and compare this with traditional osteotomies that rely on a surgeon's thorough understanding of anatomy coupled with tactile feedback to blindly guide the osteotome during surgery. A 13-year-old presented with untreated syndromic multi-suture synostosis, brachycephaly, severe exorbitism, and midface hypoplasia. For now, initial costs are high, recurring costs are relatively low, and there are perceived benefits of imaged-guided surgery as an excellent teaching tool for visualizing difficult and often unseen anatomy through computerized software and multi-planar real-time images.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.76-79
• /
• 2009

This paper investigates the performance of a vehicular rear-view camera through quantifying the image quality based on several objective criteria from the ISO (International Organization for Standardization). In addition, various experimental environments are defined considering the conditions under which a rear-view camera may need to operate. The process for evaluating the performance of a rear-view camera is composed of five objective criteria: noise test, resolution test, OECF (opto-electronic conversion function) test, color characterization test, and pincushion and barrel distortion tests. The proposed image quality quantification method then expresses the results of each test as a single value, allowing easy evaluation. In experiments, the performance evaluation results are analyzed and compared with those for a regular digital camera.