• Proceedings of the KSRS Conference
• /
• v.1
• /
• pp.500-503
• /
• 2006

To adjust the discrepancy between Light Detection and Ranging (LIDAR) strips, previous researches generally have been conducted using conjugate features, which are called feature-based approaches. However, irrespective of the type of features used, the adjustment process relies upon the existence of suitable conjugate features within the overlapping area and the ability of employed methods to detect and extract the features. These limitations make the process complex and sometimes limit the applicability of developed methodologies because of a lack of suitable features in overlapping areas. To address these drawbacks, this paper presents a methodology using area-based algorithms. This approach is based on the scheme that discrepancies make complex the local height variations of LIDAR data whithin overlapping area. This scheme can be helpful to determine an appropriate transformation for adjustment in the way that minimizes the geographical complexity. During the process, the contour tree (CT) was used to represent the geological characteristics of LIDAR points in overlapping area and the Iterative Closest Points (ICP) algorithm was applied to automatically determine parameters of transformation. After transformation, discrepancies were measured again and the results were evaluated statistically. This research provides a robust methodology without restrictions involved in methods that employ conjugate features. Our method also makes the overall adjustment process generally applicable and automated.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.37 no.1
• /
• pp.11-20
• /
• 2000

This paper presents the method of extracting the contour and shape parameters for moving object tracking in traffic scenes. The contour is extracted by applying difference image method in reduction image and the features are extracted from original image to grow the accuracy of tracking. We used features such as circle distribution, center moment, and maximum and minimum ratio. Data association problem is solved by these features. Kalman filters are used for moving object tracking on real time. The simulation results indicate that the proposed algorithm appears to generate feature vectors good enough for multiple vehicle tracking.

• Journal of Information Processing Systems
• /
• v.16 no.3
• /
• pp.663-676
• /
• 2020

Plant leaf classification is a significant application of image processing techniques in modern agriculture. In this paper, a multi-granular angle description method is proposed for plant leaf classification and retrieval. The proposed method can describe leaf information from coarse to fine using multi-granular angle features. In the proposed method, each leaf contour is partitioned first with equal arc length under different granularities. And then three kinds of angle features are derived under each granular partition of leaf contour: angle value, angle histogram, and angular ternary pattern. These multi-granular angle features can capture both local and globe information of the leaf contour, and make a comprehensive description. In leaf matching stage, the simple city block metric is used to compute the dissimilarity of each pair of leaf under different granularities. And the matching scores at different granularities are fused based on quotient space theory to obtain the final leaf similarity measurement. Plant leaf classification and retrieval experiments are conducted on two challenging leaf image databases: Swedish leaf database and Flavia leaf database. The experimental results and the comparison with state-of-the-art methods indicate that proposed method has promising classification and retrieval performance.

• Journal of Information Processing Systems
• /
• v.9 no.1
• /
• pp.103-116
• /
• 2013

Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound(TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a method for automatic prostate segmentation in TRUS images using Gabor feature extraction and snake-like contour is presented. This method involves preprocessing, extracting Gabor feature, training, and prostate segmentation. The speckle reduction for preprocessing step has been achieved by using stick filter and top-hat transform has been implemented for smoothing the contour. A Gabor filter bank for extraction of rotation-invariant texture features has been implemented. A support vector machine(SVM) for training step has been used to get each feature of prostate and nonprostate. Finally, the boundary of prostate is extracted by the snake-like contour algorithm. A number of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with less than 10.2% of the accuracy which is relative to boundary provided manually by experts.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.8
• /
• pp.1480-1486
• /
• 2002

In this study, the cross-coupling control (CCC) with three new features is proposed to maintain contour precision in high-speed nonlinear contour machining. One is an improved contour error model that provides almost exact calculation of the errors. Another is the utilization of variable controller gains based on the instantaneous curvature of the contour and the variable command. For this scheme, a stability is analyzed. As a result, the stability region is obtained, and the variable gains are decided within that region. The other scheme in the proposed CCC is a real-time feedrate adaptation module to regulate cutting force fur better surface finish through regulation of material removal rate (MRR). The simulation results show that the proposed CCC system can provide better precision than the existing method particularly in high-speed machining of nonlinear contours.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.1 no.1
• /
• pp.238-248
• /
• 1998

This paper presents an image analysis method for mearurement correction using the object contour based analysis, which measure the shape features of the imitation missile object. The image analysis is divided into object's tilting angle analysis and corner points detection. The tilting angle is calculated by edge extracting the region-of-interest image and by Radon transform it. The corner points are obtained by contour tracking of binary image and its curvature data processing and analysis. The ability of this presented method is simulated and evaluated by the results of accuracy testing.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.6
• /
• pp.593-598
• /
• 2014

Hand gesture recognition based on vision is a challenging task in human-robot interaction. The sign language of finger spelling alphabets has been tested as a kind of hand gesture. In this paper, we test hand gesture recognition by detecting the contour shape and orientation of hand with visual image. The method has three stages, the first stage of finding hand component separated from the background image, the second stage of extracting the contour feature over the hand component and the last stage of comparing the feature with the reference features in the database. Here, finger spelling alphabets are used to verify the performance of our system and our method shows good performance to discriminate finger alphabets.

• The KIPS Transactions:PartB
• /
• v.11B no.3
• /
• pp.281-288
• /
• 2004

In order to extract and analyze complex features of the behavior of animals in response to external stimuli such as toxic chemicals, we implemented an adaptive computational method to characterize changes in the behavior of chironomids in response to treatment with the insecticide, diazinon. In this paper, we propose an energy minimization model to extract the features of response behavior of chironomids under toxic treatment, which is applied on the image of velocity vectors. It is based on the improved active contour model and the variations of the energy functional, which are produced by the evolving active contour. The movement tracks of individual chironomid larvae were continuously measured in 0.25 second intervals during the survey period of 4 days before and after the treatment. Velocity on each sample track at 0.25 second intervals was collected in 15-20 minute periods and was subsequently checked to effectively reveal behavioral states of the specimens tested. Active contour was formed around each collection of velocities to gradually evolve to find the optimal boundaries of velocity collections through processes of energy minimization. The active contour which is improved by T. Chan and L. Vese is used in this paper. The energy minimization model effectively revealed characteristic patterns of behavior for the treatment versus no treatment, and identified changes in behavioral states .is the time progressed.

• Phonetics and Speech Sciences
• /
• v.7 no.1
• /
• pp.97-105
• /
• 2015

This research mainly focuses on intonational characteristics of synchronous English speech. Intonation contours were extracted from 1,848 utterances produced in two different speaking modes (solo vs. synchronous) by 28 (12 women and 16 men) native speakers of English. Synchronous speech is found to be slower than solo speech. Women are found to speak slower than men. The effect size of speech rate caused by different speaking modes is greater than gender differences. However, there is no interaction between the two factors (speaking modes vs. gender differences) in terms of speech rate. Analysis of pitch point features has it that synchronous speech has smaller Pt (pitch point movement time), Pr (pitch point pitch range), Ps (pitch point slope) and Pd (pitch point distance) than solo speech. There is no interaction between the two factors (speaking modes vs. gender differences) in terms of pitch point features. Analysis of sentence level features reveals that synchronous speech has smaller Sr (sentence level pitch range), Ss (sentence slope), MaxNr (normalized maximum pitch) and MinNr (normalized minimum pitch) but greater Min (minimum pitch) and Sd (sentence duration) than solo speech. It is also shown that the higher the Mid (median pitch), the MaxNr and the MinNr in solo speaking mode, the more they are reduced in synchronous speaking mode. Max, Min and Mid show greater speaker discriminability than other features.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.12B
• /
• pp.2359-2368
• /
• 1999

In this paper we propose a 2D FLIR image-based 3D target recognition system which performs group-to-ground vehicle recognition using the target contour and its degree of reliability extracted from FLIR image. First we extract target from background in FLIR image. Then we define contour points of the extracted target which have high edge gradient magnitude and brightness value as reliable contour point and make reliable contour by grouping all reliable contour points. After that we extract corresponding reliable contours from model contour image and perform comparison between scene and model features which are calculated by DST(discrete sine transform) of reliable contours. Experiment shows that the proposed algorithm work well and even in case of imperfect target extraction it showed better performance then conventional 2D contour-based matching algorithms.