• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.141-148
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• 2011

Most of the previous works on scene change detection algorithm focus on the detection of abrupt rather than gradual changes. In general, gradual scene change detection algorithms require heavy computation. Some of those approaches don't consider the error factors such as flashlights, camera or object movements, and special effects. Many scenes change detection algorithms based on the histogram show better performances than other approaches, but they have computation load problem. In this paper, we proposed a scene change detection algorithm with fast and accurate performance using the vertical and horizontal blocked slice images and their macro block informations. We apply graph cut partitioning algorithm for clustering and partitioning of video sequence using generated spatio-temporal histogram. When making spatio-temporal histogram, we only use the central block on vertical and horizontal direction for performance improvement. To detect camera and object movement as well as various special effects accurately, we utilize the motion vector and type information of the macro block.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.234-243
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• 2006

The recent rapid development of HCI and surveillance technologies has brought great interests in application systems to process faces. Much of research efforts in these systems has been primarily focused on such areas as face recognition, facial expression analysis and facial feature extraction. However, not many approaches have been reported toward face direction detection. This paper proposes a method to detect the direction of a face using a facial feature called facial triangle, which is formed by two eyebrows and the lower lip. Specifically, based on the single monocular view of the face, the proposed method introduces very simple formulas to estimate the horizontal or vertical rotation angle of the face. The horizontal rotation angle can be calculated by using a ratio between the areas of left and right facial triangles, while the vertical angle can be obtained from a ratio between the base and height of facial triangle. Experimental results showed that our method makes it possible to obtain the horizontal angle within an error tolerance of ${\pm}1.68^{\circ}$, and that it performs better as the magnitude of the vertical rotation angle increases.

• Journal of Sensor Science and Technology
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• v.12 no.2
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• pp.57-65
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• 2003

When a vision chip for edge detection using CMOS process is designed, there is a necessity to implement local light adaptive-function for detecting distinctive features of an image at a wide range of light intensities. Local light adaptation is to achive the almost same output level by changing the size of receptive-fields of the local horizontal cell layers according to input light intensities, based on the lateral inhibitive-function of the horizontal cell. Thus, the almost same output level can be obtained whether input light intensities are much or less larger than background. In this paper, the horizontal cells using a resistive network which consists of p-MOSFETs were modeled and analyzed, and the local light adaptive-mechanism of the designed vision chip using the resistive network was verified.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.46-49
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• 2002

One problem of vision-based eye-gazed detection is that it gives low resolution. Base on the displacement of the eyes, we proposed method for vision-based eye-gaze detection. While looking at difference positions on the screen, the distance of the centers of the eyes change accordingly. This relationship is derived and used to map the displacement to the distance in the screen. The experiments are performed to measure the accuracy and resolution to verify the proposed method. The results shown the accuracy of the screen mapping function for the horizontal plane are 76.47% and the error of this function be 23.53%

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.2
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• pp.57-62
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• 1996

Basically, the idea underlying most edge-detection technique is the computation of a local derivative operator used for edge detection in gray level image. This concept can be easily illustrated with the aid of object which shows an image of a simple lilght on a dark background, Using the gray level profile along a horizontal scan line of the image. the first and second derivatives of it were acquired. This study is to develop an automatic measuring system based on the digital image processing which can be applied to the real time measurement of the characteristics of the ultra-thin thickness. The experimental results indicate that the developed automatic inspection can be applied in real situation.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.148-150
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• 2006

In this paper, we propose a new method for detection of mass-type breast cancer in dense mammogram. As the proposed method analyzes texture of the breast tissue using method by fusing Homogeneity and Ranklets, improve problem of traditional method. Homogeneity gives the measure of uniform density, and Ranklets determine orientation selective property at vertical, horizontal and diagonal in mass region. The proposed method is suitable to dense mammogram with tangled normal tissue and cancer tissue. SVM(Support Vector Machine) classifier is used for effective detection of mass-type breast cancer in dense mammogram.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.1
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• pp.79-85
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• 2017

In this paper, several optimizations are proposed to enhance the quality of lane detection algorithms in automotive applications. Considering the diagonal directions of lanes, the proposed limited Hough transform newly introduces image-splitting and angle-limiting schemes that relax the number of possible angles at the line voting process. In addition, unnecessary edges along the horizontal and vertical directions are pre-defined and removed during the edge detection procedures, increasing the detecting accuracy remarkably. Simulation results shows that the proposed lane recognition algorithm achieves an accuracy of more than 90% and a computing speed of 92 frame/sec, which are superior to the results from the previous algorithms.

• Journal of the Optical Society of Korea
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• v.17 no.2
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• pp.188-199
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• 2013

This paper presents a novel algorithm for nighttime detection of the lane markers painted on a road at night. First of all, the proposed algorithm uses neighborhood average filtering, 8-directional Sobel operator and thresholding segmentation based on OTSU's to handle raw lane images taken from a digital CCD camera. Secondly, combining intensity map and gradient map, we analyze the distribution features of pixels on boundaries of lanes in the nighttime and construct 4 feature sets for these points, which are helpful to supply with sufficient data related to lane boundaries to detect lane markers much more robustly. Then, the searching method in multiple directions- horizontal, vertical and diagonal directions, is conducted to eliminate the noise points on lane boundaries. Adapted Hough transformation is utilized to obtain the feature parameters related to the lane edge. The proposed algorithm can not only significantly improve detection performance for the lane marker, but it requires less computational power. Finally, the algorithm is proved to be reliable and robust in lane detection in a nighttime scenario.

• Progress in Superconductivity
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• v.14 no.2
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• pp.82-86
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• 2012

A sensitive eight-channel high-Tc Superconducting Interference Device (SQUID) detection system for magnetic contaminant in a lithium ion battery anode was developed. Finding ultra-small metallic foreign matter is an important issue for a manufacturer because metallic contaminants carry the risk of an internal short. When contamination occurs, the manufacturer of the product suffers a great loss from recalling the tainted product. Metallic particles with outer dimensions smaller than 100 microns cannot be detected using a conventional X-ray imaging system. Therefore, a highly sensitive detection system for small foreign matter is required. We have already developed a detection system based on a single-channel SQUID gradiometer and horizontal magnetization. For practical use, the detection width of the system should be increased to at least 65 mm by employing multiple sensors. In this paper, we present an 8-ch high-Tc SQUID roll-to-roll system for inspecting a lithium-ion battery anode with a width of 65 mm. A special microscopic type of a cryostat was developed upon which eight SQUID gradiometers were mounted. As a result, small iron particles of 35 microns on a real lithium-ion battery anode with a width of 70 mm were successfully detected. This system is practical for the detection of contaminants in a lithium ion battery anode sheet.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.506-512
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• 2003

The edge detection has been so far under a lot of studies on its methods, as a very important part of image recognition. Never the less the correct detection of the edge has been yet a difficult problem because of the various scopes of detection according to the applied field. One of those problems to be solved is the edge detection in images with noise. This paper presents an efficient method which removes noise and detect edge in the same framework based on fuzzy logic. The method consists of two steps. First, an efficient filtering is applied to eliminate the noise from original image. The filtering is performed by utilizing fuzzy MIN-MAX operator in three directions such as vertical, horizontal and diagonal angle of 3${\times}$3 mask. Second, edges are detected by using extended fuzzy Shanon Function.