• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.5
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• pp.133-138
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• 2010

In this paper, we make up a feature image including spatial properties and statistical properties on image, and format covariance matrices using region variance magnitudes. By using it to texture classification, this paper puts a proposal for tough texture classification way to illumination, noise and rotation. Also we offer a way to minimalize performance time of texture classification using integral image expressing middle image for fast calculation of region sum. To estimate performance evaluation of proposed way, this paper use a Brodatz texture image, and so conduct a noise addition and histogram specification and create rotation image. And then we conduct an experiment and get better performance over 96%.

• Applied Microscopy
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• v.33 no.3
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• pp.187-193
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• 2003

When electron microscope images and selected area diffraction patterns of crystalline materials are being compared, it is important to know for the rotation of the diffraction pattern with respect to the image caused by the magnetic lens in the Electron Microscope. A well-known method to determine this rotation is to use a test crystal of $MoO_3$. But this method of determination of the rotation angle contains an uncertainty of $180^{\circ}$. Thus one has to devise another way to eliminate this uncertainty. In this paper we present a new and simple method of determining this rotation without any complexity. The method involves a process of obtaining LACBED patterns of crystalline materials. For the J2010 electron microscope, the rotation is determined to be $180^{\circ}$ and this angle remains unchanged for changing of the magnification and the camera length.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.251-254
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• 2000

This paper proposes an enhanced algorithm for person identification system utilizing hand vein pattern. The conventional algorithm does not cope with distortion caused by image rotation caused by misplaced hands on the imaging device. A straightforward approach to consider the rotaional compensation required too much computational load, thus, we devised an approach to expect the rotation direction along with image translation, reducing the compuational requirement dramatically In this paper, we present the details of the algorithm with experimental results with the new algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.10
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• pp.431-438
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• 2015

In this paper we address the symmetric-invariant problem in boundary image matching. Supporting symmetric transformation is an important factor in boundary image matching to get more intuitive and more accurate matching results. However, the previous boundary image matching handled rotation transformation only without considering symmetric transformation. In this paper, we propose symmetric-invariant boundary image matching which supports the symmetric transformation as well as the rotation transformation. For this, we define the concept of image symmetry and formally prove that rotation-invariant matching of using a symmetric image always returns the same result for every symmetric angle. For efficient symmetric transformation, we also present how to efficiently extract the symmetric time-series from an image boundary. Finally, we formally prove that our symmetric-invariant matching produces the same result for two approaches: one is using the time-series extracted from the symmetric image; another is using the time-series directly obtained from the original image time-series by symmetric transformation. Experimental results show that the proposed symmetric-invariant boundary image matching obtains more accurate and intuitive results than the previous rotation-invariant boundary image matching. These results mean that our symmetric-invariant solution is an excellent approach that solves the image symmetry problem in time-series domain.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.3
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• pp.1114-1121
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• 2012

There is a cause and effect relationship in that brain injury causes impairment of mental rotation and ultimately independent functional activities. The purpose of this study was to compare the effects of mental rotation on reaction time and precision between the normal adults and chronic hemiparetic stroke patients. Thirty-one patients with chronic hemiparetic stroke and twenty normal adults participated in this study. The participants conducted 2 types of tasks for mental rotation: a comparison task using mirror images, and a rotation task using angular disparity images for 2 different 3-dimensional objects. Each of the 3 possible angled shapes ($90^{\circ}$, $180^{\circ}$, and $270^{\circ}$) appeared in each pair. The test consisted of 6 mirror-reflected image pairs and 6 angular disparity image pairs visualized during angular rotation, and 12 test periods. The subjects were judged on how accurately and rapidly they could distinguish between the mirrored and non-mirrored pairs. The study measured reaction time and precision to compare the effect of mental rotation tasks. Reaction time during all 3 angular conditions were significantly longer in the stroke patients than that in the normal adult during the comparison tasks and the rotation tasks. In addition, precision during mental rotation tasks was not significantly different between normal adults and stroke patients. Our results suggest that rehabilitation therapists should keep in mind that mental rotation is more difficult in stroke population than in normal adults.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.943-946
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• 1998

In this paper, we applied FFT to PCB Images, cutting unnecessary singals and noise, moving the starting point to center of image and used rotaion transform. from the detected edge Hough Transform identify the length, but not the angle, so we matched PCB images with using rotation transform to identify length and angle. After rotation transform we employ Least Squared Method to exact stereo matching.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.225-229
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• 2020

Recently, convolutional neural network (CNN) have been showed outstanding performance in the field of image recognition, image processing and computer vision, etc. In this paper, we propose a CNN-based image rotation correction algorithm as a solution to image rotation problem, which is one of the factors that reduce the recognition rate in image recognition system using CNN. In this paper, we trained our deep learning model with Leeds Sports Pose dataset to extract the information of the rotated angle, which is randomly set in specific range. The trained model is evaluated with mean absolute error (MAE) value over 100 test data images, and it is obtained 4.5951.

• Journal of the Korea Computer Industry Society
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• v.4 no.10
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• pp.643-654
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• 2003

This paper proposes slippage and rotation sensing method in tactile image of robot griper. To overcome the demerits of inaccurate taxel positional sensing generated by previous moment method and edge ＆ line method according to constraints of taxet number changing or minimum taxel number, the proposed method classified the sensing method into two classes such as pixel status analysis and decision factor determination. The decision factor determines taxel threshold for filtering and sensing method choice based on moment method and edge ＆ line method. Computer simulations and experiment result show that the proposed method enhances the slippage and rotation sensing than previous methods for tactile image.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2006.06a
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• pp.730-736
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• 2006

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 ill 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 technique, instead of embedding in the normalized image. Conventional rotation resistant schemes that use full frame transform. In this paper, we adopt $8{\times}8$ block 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
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• 2013.05a
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• pp.385-388
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• 2013

In this paper, we show the weakness of the image matching method by using MPEG-7 EHD(Edge Histogram Descriptor) and suggest how to improve this weakness by using image normalization. EHD algorithm is an image matching technique that collects edge's slope of distribution and same distribution. However, the EHD error rate is high because EHD is sensitive for changes of object distortion and rotation that will be matched. We improve matching performance by accurately extract edge information in image by using normalization. We compare and analyze the normalized EHD algorithm by using distortion and rotation and it shows robustness for changes of the size and rotation.