• Journal of the Korea Society of Computer and Information
• /
• 제16권8호
• /
• pp.95-101
• /
• 2011

In this paper, using pixel connectivity tracking feature to remove a doctor has been studied. Feature extraction method is a method using the crossing. However, by crossing a lot of feature extraction method sis a doctor. Extracted using the method of crossing the wrong feature to remove them from the downside and the eight pixels around the fork to trace if it satisfies the conditions in the actual feature extraction and feature conditions are not satisfied because the doctor was removed. To evaluate the performance using crossing methods and extracted using pixel connectivity trace was compared to the actual feature, the experimental results using pixel connectivity trace arcuate sentence, croissants sentence, sentence the defrost feature on your doctor about47%, respectively, 40%, 30%were found to remove.

• Journal of the Korea Society of Computer and Information
• /
• 제15권2호
• /
• pp.55-64
• /
• 2010

This paper proposes a face detection method using Free Rectangle feature which possesses a quick execution time and a high efficiency. The proposed mask of Free Rectangle feature is composed of two separable rectangles with the same area. In order to increase the feature diversity, Haar-like feature generally uses a complex mask composed of two or more rectangles. But the proposed feature mask can get a lot of very efficient features according to any position and scale of two rectangles on the feature window. Moreover, the Free Rectangle feature can largely reduce the execution time since it is defined as the only difference of the sum of pixels of two rectangles irrespective of the mask type. Since it yields a quick detection speed and good detection rates on real world images, the proposed face detection method based on Adaboost algorithm is easily applied to detect another object by changing the training dataset.

• Journal of the Korea Society of Computer and Information
• /
• 제18권1호
• /
• pp.123-136
• /
• 2013

The Feature model can not be guaranteed the syntactic accuracy of its model and be difficult the validation using automatic tool for its syntax, because this model is expressed by a graphical and informal structure in itself. Therefore, there is a need to formalize and check for the feature model, to precisely define syntax for construct of the model. This paper presents a Z formal specification and a model checking mechanism of the feature model to guarantee the correctness of the model. It first defines the translation rules between feature model and Z, and then converts the syntax of the feature model into the Z schema specification by applying these rules. Finally, the Z schema specification is checked syntax, type, and domain errors using the Z/Eves validation tool to assure the correctness of its specification, With the use of the proposed method, we may express more precisely the construct of the feature model. Moreover the domain analyst are able to usefully verify the errors of the generated feature model.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• 제17권1호
• /
• pp.733-744
• /
• 2016

The legacy methods for converting a business model to a feature model make it difficult to support an automatic transformation due to a dependence on a domain analyzers' intuitions, which hinders the feature oriented development for the integration of feature modeling in business modeling. This paper proposes a method for converting a BPMN business model into a feature model based on syntax. To allow the conversion between the heterogeneous models from BPMN to the FM(Feature Model), it defines the grouping mechanism based activities' syntax, and then makes translation rules and a method based on the element (represent business function) and structure (relationships and process among elements), which are common constructs of their models. This method was applied to an online shopping mall system as a case study. With this mechanism, it will help develop a mechanical or automated structure transformation from the BPMN model to the FM.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 한국정보통신학회 2022년도 추계학술대회
• /
• pp.256-257
• /
• 2022

In this paper, we introduce a method of extracting three-dimensional feature points through the movement of a single mobile device. Using a monocular camera, a 2D image is acquired according to the camera movement and a baseline is estimated. Perform stereo matching based on feature points. A feature point and a descriptor are acquired, and the feature point is matched. Using the matched feature points, the disparity is calculated and a depth value is generated. The 3D feature point is updated according to the camera movement. Finally, the feature point is reset at the time of scene change by using scene change detection. Through the above process, an average of 73.5% of additional storage space can be secured in the key point database. By applying the algorithm proposed to the depth ground truth value of the TUM Dataset and the RGB image, it was confirmed that the\re was an average distance difference of 26.88mm compared with the 3D feature point result.

• Journal of the Korea Society of Computer and Information
• /
• 제15권11호
• /
• pp.75-82
• /
• 2010

The paper proposed CBIRS/EFI with contents based search technique using edge feature information of the object from image information of the object which is uncertain. In order to search specially efficiently case of partial image information of the object, we used the search technique which extracts outline information and color information in feature information of object. In order to experiment this, we extracted side edge feature information of the vehicle for feature information of the object after capture the car image of the underground garage. This is the system which applies a contents base search by the result which analyzes the image which extracts a feature, an original image to search and a last similar measurement result. This system compared in FE-CBIRS systems which are an existing feature extraction contents base image retrieval system and the function which improves the accuracy and an effectiveness of search rate was complemented. The performance appraisal of CBIRS/EFI systems applied edge extraction feature information and color information of the cars. And we compared a color feature search time, a shape characteristic search time and a search rate from the process which searches area feature information. We extracted the case 91.84% of car edge feature extraction rate. And a average search time of CBIRS/EFI is showing a difference of average 0.4-0.9 seconds than FE-CBIRS from vehicle. color search time, shape characteristic search time and similar search time. So, it was proven with the fact that is excellent.

• Journal of the Korea Society of Computer and Information
• /
• 제13권5호
• /
• pp.53-67
• /
• 2008

At present, for reuse of similar domains between feature model and class model. researches of transformation at the model level and of transformation using ontology between two models are being made. but consistent transformation through metamodel is not made. And the factors of modeling transformation targets are not sufficient, and especially, automatic transformation algorithm and supporting tools are not provided so reuse of domains between models is not activated. This paper proposes a method of transformation from feature model to class model using ontology on the metamodel. For this, it re-establishes the metamodel of feature model, class model, and ontology, and it defines the properties of modelling factors for each metamodel. Based on the properties, it defines the profiles of transformation rules between feature mndel and ontology, and between ontology and class model, using set theory and propositional calculus. For automation of the transformation, it creates transformation algorithm and supporting tools. Using the proposed transformation rules and tools, real application is made through Electronic Approval System. Through this, it is possible to transform from the existing constructed feature model to the class model and to use it again for a different development method. Especially, it is Possible to remove ambiguity of semantic transformation using ontology, and automation of transformation maintains consistence between models.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.2209-2212
• /
• 2003

In this paper, we propose the method to extract the important frequency bands from the EMG signal, and for generation of feature vector using the important frequency bands. The EMG signal is measured with 4 sensor and is recorded as 4 channel’s time series data. The same frequency bands from 4 channel’s frequency components are selected as the important frequency bands. The feature vector is calculated by the function formed using the combination of selected same important frequency bands. The EMG signals acquired from seven wrist motion type are recognized by changing into the feature vector formed. Then, the extraction and generation is performed by using the double combination of the genetic algorithm (GA) and the neural network (NN). Finally, in order to illustrate the effectiveness of the proposed method, computer simulations are done.

• IEMEK Journal of Embedded Systems and Applications
• /
• 제12권6호
• /
• pp.395-403
• /
• 2017

Image processing for object detection and identification has been studied for supply chain management application with various approaches. Among them, feature pointed detection algorithm is used to track an object or to recognize a position in automated supply chain systems and a depth image based feature point detection is recently highlighted in the application. The result of feature point detection is easily influenced by image noise. Also, the depth image has noise itself and it also affects to the accuracy of the detection results. In order to solve these problems, we propose a novel hybrid filtering mechanism for depth image based feature point detection, it shows better performance compared with conventional hybrid filtering mechanism.

• The Journal of Korea Robotics Society
• /
• 제11권1호
• /
• pp.33-40
• /
• 2016

In this paper, we propose a method for estimating the pose of the camera using a rectangle feature utilized for the visual SLAM. A warped rectangle feature as a quadrilateral in the image by the perspective transformation is reconstructed by the Coupled Line Camera algorithm. In order to fully reconstruct a rectangle in the real world coordinate, the distance between the features and the camera is needed. The distance in the real world coordinate can be measured by using a stereo camera. Using properties of the line camera, the physical size of the rectangle feature can be induced from the distance. The correspondence between the quadrilateral in the image and the rectangle in the real world coordinate can restore the relative pose between the camera and the feature through obtaining the homography. In order to evaluate the performance, we analyzed the result of proposed method with its reference pose in Gazebo robot simulator.