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

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.837-838
• /
• 2008

This paper presents a new signature and Fourier descriptor based algorithm for recognizing a rotated object and its rotation angle. Fourier descriptor is used to represent an object using its frequence parameters which are not influenced by rotation. once the object is recognized, the point with the largest auto-correlation coefficient which can be calculated from signature of the object is used to find angle of the object. The outstanding performance of the proposed algorithm has been tested with the test images where more than 10 2D objects arbitrarily located on a table.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.8
• /
• pp.3820-3841
• /
• 2018

Most of the accidents occur due to drowsiness while driving, avoiding road signs and due to driver's distraction. Driver's distraction depends on various factors which include talking with passengers while driving, mood disorder, nervousness, anger, over-excitement, anxiety, loud music, illness, fatigue and different driver's head rotations due to change in yaw, pitch and roll angle. The contribution of this paper is two-fold. Firstly, a data set is generated for conducting different experiments on driver's distraction. Secondly, novel approaches are presented that use features based on facial points; especially the features computed using motion vectors and interpolation to detect a special type of driver's distraction, i.e., driver's head rotation due to change in yaw angle. These facial points are detected by Active Shape Model (ASM) and Boosted Regression with Markov Networks (BoRMaN). Various types of classifiers are trained and tested on different frames to decide about a driver's distraction. These approaches are also scale invariant. The results show that the approach that uses the novel ideas of motion vectors and interpolation outperforms other approaches in detection of driver's head rotation. We are able to achieve a percentage accuracy of 98.45 using Neural Network.

• Journal of the Korean Society of Safety
• /
• v.31 no.3
• /
• pp.28-33
• /
• 2016

Since defects in the wheels of railway vehicles, which occur due to wears with the rail, cause serious damage to the running device, the diagnostic monitoring system for condition-based maintenance is required to secure the driving safety. In this paper, we studied to apply a useful Cepstrum analysis to detect periodic structure in spectrum among the vibration signal processing techniques for the fault diagnosis of a rotating body such as wheel. In order to analyze in variations of train velocity, the Cepstrum analysis was performed after a domain change of the vibration signal from time domain to rotation angle domain. When domains change, it is important to use a interpolation for a uniform interval of the rotation angle. Finally, the Cepstrum analysis for wheel flat detection was verified by using the vibration signal including the disturbance resulting from the rail irregularities and the vibration of bogie components.

• Journal of IKEEE
• /
• v.20 no.4
• /
• pp.344-350
• /
• 2016

In this Paper, we propose an optimized method of hardware design based on Field Programmable Gate Array (FPGA) to detect rotated angle of high definition image about Extreme Contour Point (ECP) algorithm with moving video image could be not happened to translation motion, but also physical rotation motion. It was evaluated by XC7Z020 xc7z020-3clg400 FPGA board by using xilinx 14.2 tool. The much well-known method, the Coordinate Rotation Digital Integrated Computation (CORDIC) is an algorithm to estimate rotated angle between point and point. Through the result both ECP and CORDIC, our proposed design are confirmed to have similar operating speed of about 4ns with CORDIC. However, it is verified to have high performance result in terms of the hardware cost, is much better than CORDIC with cost reduction of registers and Look Up Tables (LUTs) of 108% and 91%, respectively.

• Journal of Information Technology Applications and Management
• /
• v.14 no.1
• /
• pp.137-144
• /
• 2007

In this paper, we propose a rotation resistant robust logo embedding watermarking technique. Geometric manipulations make the detection process very complex and difficult. Watermark embedding in the normalized image directly suffers from smoothing effect due to the interpolation during the image normalization. This can be avoided by estimating the transform parameters using image normalization angle and moments, instead of embedding in the normalized image. Conventional rotation resistant schemes that use full frame transform. In this paper we adopt DCT and calculate masking using a spatio-frequency localization of the $8{\times}8$ block DCT coefficients. Experimental results show that the proposed algorithm is robust against rotation process.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.05a
• /
• pp.252-254
• /
• 2017

Tire is one of the most important to drive cars. There is high possibility to occur slip phenomenon and to increase braking distance depending on tire wear. Therefore, you should be check tire wear and replace tires periodically. In the past, most people manually check the wear level and judged whether or not to replace the tire. But, since the standard is different for each person, the replacement cycle becomes unclear. Since a clear replacement cycle is established, it is expected that the accident rate of a vehicle caused by a tire will be reduced. Therefore, i propose detection method for a tire wear using a motor rotation angle.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.28B no.5
• /
• pp.327-334
• /
• 1991

This paper proposes an efficient method of implementing the generalized Hough transform (GHT), which has been hindered by an excessive computing load and a large memory requirement. The conventional algorithm requires a parameter space of 4 dimensions in detection a rotated, scaled, and translated object in an input image. Prior to the application of GHT to the input image, the proposed method determines the angle of rotation and the scaling factor of the test image using the proportion of the edge components between the reference image and test image. With the rotation angle and the scaling factor already determined, the parameter spaceis to be reduced to a simple array of 2 dimensions by applying the unit GHT only one time. The experiments with the image of airplanes reveal that both of the computing time and the requires memory size are reduced by 95 percent, without any degradatationof accuracy, compared with the conventional GHT algorithm.

• Journal of Magnetics
• /
• v.18 no.4
• /
• pp.454-459
• /
• 2013

This paper deals with an optimal angle error reduction method of magnetic position sensor using hall effect elements. The angle detection simulation for the magnetic position sensor is performed by 3 dimensional finite element method and Taguchi method, one of the design of experiments. The magnetic position sensor is required to generate ideal sine and cosine waveforms from its hall effect elements according to rotation angle for precise angle information. However, the output signals are easy to include harmonics due to uneven magnetic field distribution from permanent magnet in the air-gap in the vicinity of hall effect elements. For the Taguchi method, three design parameters related to position of hall effect elements and shape of back yoke are selected. The characteristics of optimal magnetic position sensor are compared with those of original one in terms of simulation as well as experiment. Finally, the performances of the motor adopting original model and optimal model are represented for the purpose of verification of motor performance due to signals from magnetic position sensor.

• Korean Journal of Optics and Photonics
• /
• v.3 no.2
• /
• pp.105-110
• /
• 1992

In order to measure fine rotation angles by magneto-optic effects of magneto-optical recording thin films, a polarization modulation method is used. In the experiment, the polarization of laser (He-Ne laser) beam is modulated by a Faraday rotator and the amplified modulated signals are selectively detected by phase sensitive detector. The magnetic Kerr rotation and Faraday rotation hysteresis loops are investigated by this method for thermally evaporated amorphous TbFeCo thin films and RF sputtered garnet thin films. Rotation angles about $0.25^{\circ}$ are measured easily from TaFeCo thin films. In the case of longitudinal Kerr rotation, very small rotation angle of $2.5\times10^{-3^\circ}$ is measured with good accuracy of the measurement (about $1\times10^{-3^\circ}$). And it is found that each thin films have the hysteresis curves of high coercivity and good squareness.