• 대한의용생체공학회:의공학회지
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• 제43권6호
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• pp.441-447
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• 2022

In this paper, we propose a pill identification model using engraved text feature and image feature such as shape and color, and compare it with an identification model that does not use engraved text feature to verify the possibility of improving identification performance by improving recognition rate of the engraved text. The data consisted of 100 classes and used 10 images per class. The engraved text feature was acquired through Keras OCR based on deep learning and 1D CNN, and the image feature was acquired through 2D CNN. According to the identification results, the accuracy of the text recognition model was 90%. The accuracy of the comparative model and the proposed model was 91.9% and 97.6%. The accuracy, precision, recall, and F1-score of the proposed model were better than those of the comparative model in terms of statistical significance. As a result, we confirmed that the expansion of the range of feature improved the performance of the identification model.

• 한국CDE학회논문집
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• 제1권2호
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• pp.133-149
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• 1996

In order to reduce the trial-and-errors in design and production of injection molded plastic parts, there has been much research effort not only on CAE systems which simulate the injection molding process, but also on CAD systems which support initial design and re-design of plastic parts and their molds. The CAD systems and CAE systems have been developed independently with being built on different basis. That is, CAD systems manipulate the part shapes and the design features in a complete solid model, while CAE systems work on shell meshes generated on the abstract sheet model or medial surface of the part. Therefore, it is required to support the two types of geometric models and feature information in one environment to integrate CAD and CAE systems for accelerating the design speed. A feature-based non-manifold geometric modeling system has been developed to provide an integrated environment for design and analysis of injection molding products. In this system, the geometric models for CAD and CAE systems are represented by a non-manifold boundary representation and they are merged into a single geometric model. The suitable form of geometric model for any application can be extracted from this model. In addition, the feature deletion and interaction problem of the feature-based design system has been solved clearly by introducing the non-manifold Boolean operation based on 'merge and selection' algorithm. The sheet modeling capabilities were also developed for easy modeling of thin plastic parts.

• 한국CDE학회논문집
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• 제11권3호
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• pp.164-171
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• 2006

As collaborative design and configuration design are of increasing importance in product development, it becomes essential to exchange the feature and parametric CAD models among participants. A history-based parametric method has been proposed and implemented. But each translator which exchanges the feature and parametric information tends to be heavy because to implement duplicated functions such as the identification of the selected geometries, mapping between features which have different attributes. Furthermore. because the history-based parametric translator uses the procedural model as the neutral format, which is the XML macro file, the history-based parametric translators need a geometric modeling kernel to generate an internal explicit geometric model. To ease the problem, we implemented a shared integration platform, the TransCAD. The TransCAD separates translators from the XML macro files. The translators for various CAD systems need to communicate with only the TransCAD. To support the communication with the TransCAD, we exposed the functions of the TransCAD by using the Automation APIs, which is developed by Microsoft. The Automation APIs of the TransCAD consist of the part modeling functions, the data extraction functions, and the utility functions. Each translator uses these functions to translate a parametric CAD model from the sending CAD system into the XML format, or from the in format into the model of the receiving CAD system This paper introduces what the TransCAD is and how it works for the exchange of the feature and parametric models.

• 한국CDE학회논문집
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• 제16권3호
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• pp.178-186
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• 2011

Static CAD models are the CAD models that do not have feature information and modeling history. These static models are generated by translating CAD models in a specific CAD system into neutral formats such as STEP and IGES. When a CAD model is translated into a neutral format, its precious feature information such as feature parameters and modeling history is lost. Once the feature information is lost, the advantage of feature based modeling is not valid any longer, and modification for the model is purely dependent on geometric and topological manipulations. However, the capabilities of the existing methods to modify static CAD models are limited, Direct modification methods such as tweaking can only handle the modifications that do not involve topological changes. There was also an approach to modify static CAD model by using volume decomposition. However, this approach was also limited to modifications of protrusion features. To address this problem, we extend the volume decomposition approach to handle not only protrusion features but also depression features in a static CAD model. This method first generates the model that contains the volume of depression feature using the bounding box of a static CAD model. The difference between the model and the bounding box is selectively decomposed into so called the feature volume and the base volume. A modification of depression feature is achieved by manipulating the feature volume of the static CAD model.

• 한국CDE학회논문집
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• 제4권2호
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• pp.139-152
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• 1999

This paper presents a feature-based approach to extracting machining features fro a feature-based design model. In the approach, a design feature to machining feature conversion process incrementally converts each added design feature into a machining feature or a set of machining features. The proposed approach an efficiently handle protrusion features and interacting features since it takes advantage of design feature information, design intent, and functional requirements during feature extraction. Protrusion features cannot be directly mapped into machining features so that the removal volumes surrounding protrusion features are extracted and converted it no machining features. By utilizing feature information as well as geometry information during feature extraction, the proposed approach can easily overcome inherent problems relating to feature recognition such as feature interactions and loss of design intent. In addition, a feature extraction process can be simplified, and a large set of complex part can be handled with ease.

• 한국CDE학회논문집
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• 제12권4호
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• pp.245-254
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• 2007

This research proposed feature extraction algorithms as an input of STEP Ap214 data, and feature parameterization process to simplify further design change and maintenance. The procedure starts with suppression of blend faces of an input solid model to generate its simplified model, where both constant and variable-radius blends are considered. Most existing cell decomposition algorithms utilize concave edges, and they usually require complex procedures and computing time in recomposing the cells. The proposed algorithm using reference features, however, was found to be more efficient through testing with a few sample cases. In addition, the algorithm is able to recognize depression features, which is another strong point compared to the existing cell decomposition approaches. The proposed algorithm was implemented on a commercial CAD system and tested with selected industrial product models, along with parameterization of recognized features for further design change.

• 한국CDE학회논문집
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• 제15권3호
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• pp.243-252
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• 2010

This paper describes a new practical simplification method for feature-based solid models. In this approach, a solid model created using feature modeling operations is first simplified by the suppression of detailed features, and then, if necessary, the model is converted to a surface model to facilitate its modification. Finally, the simplified surface model is delivered to analysis packages. The algorithm was implemented based on CATIA V.5 and applied to mid-surface generation of plastic parts for structural analysis to prove the validity and usefulness.

• 한국CDE학회논문집
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• 제16권1호
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• pp.21-30
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• 2011

Similarity assessment of a CAD model is one of important issues from the aspect of model re-using. In real practice, many new mechanical parts are designed by modifying existing ones. The reuse of part enables to save design time and efforts for the designers. Design time would be further reduced if there were an efficient way to search for existing similar designs. This paper proposes an efficient algorithm of similarity assessment for mechanical part model with design history embedded within the CAD model. Since it is possible to retrieve the design history and detailed-feature information using CAD API, we can obtain an accurate and reliable assessment result. For our purpose, our assessment algorithm can be divided by two: (1) we select suitable parts by comparing MSG (Model Signature Graph) extracted from a base feature of the required model; (2) detailed-features' similarities are assessed with their own attributes and reference structures. In addition, we also propose a indexing method for managing a model database in the last part of this article.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2824-2838
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• 2013

There has been a lot of attention paid recently to analyze dynamic human gestures that vary over time. Most attention to dynamic gestures concerns with spatio-temporal features, as compared to analyzing each frame of gestures separately. For accurate dynamic gesture recognition, motion feature extraction algorithms need to find representative features that uniquely identify time-varying gestures. This paper proposes a new feature-extraction algorithm using temporal self-similarity based on a hierarchical human model. Because a conventional temporal self-similarity method computes a whole movement among the continuous frames, the conventional temporal self-similarity method cannot recognize different gestures with the same amount of movement. The proposed model-based temporal self-similarity method groups body parts of a hierarchical model into several sets and calculates movements for each set. While recognition results can depend on how the sets are made, the best way to find optimal sets is to separate frequently used body parts from less-used body parts. Then, we apply a multiclass support vector machine whose optimization algorithm is based on structural support vector machines. In this paper, the effectiveness of the proposed feature extraction algorithm is demonstrated in an application for taebo gesture recognition. We show that the model-based temporal self-similarity method can overcome the shortcomings of the conventional temporal self-similarity method and the recognition results of the model-based method are superior to that of the conventional method.

• 전자공학회논문지SC
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• 제45권6호
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• pp.67-76
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• 2008

성공적인 상업화를 위해서는 다양한 조명 환경에서 신뢰성 있는 얼굴 인식이 필요하다. 특징 벡터 기반 얼굴 인식에서 특징 벡터를 잘 선택하는 것은 중요하다. 가버 특징 벡터는 다른 특징 벡터보다도 상대적으로 방향, 자세, 조명 등의 영향을 덜 받는 것으로 잘 알려져 있어 얼굴 인식의 특징 벡터로 많이 이용된다. 그러나 조명의 영향에 대해 완전히 독립적이지 못하다. 본 논문에서는 얼굴 이미지의 가버 특징 벡터에 대한 조명 PCA 모델의 구성을 제안하고 이를 이용하여 조명에 독립적인 얼굴 고유의 특성을 나타내는 가버 특징 벡터만을 분리해내고 이를 이용한 얼굴 인식 방법을 제시한다. 가버 특징 벡터 조명 PCA 모델은 가버 특징 벡터공간을 조명 영향 부분공간과 얼굴 고유특성 부분공간의 직교 분해로 구성한다. 얼굴 고유특성 부분공간으로 투영하여 얻어진 가버 특징 벡터는 조명 영향을 분리해 내었기 때문에 이를 이용한 얼굴 인식은 조명에 보다 강인하게 된다. 실험을 통해서 가버 특징 벡터 조명 PCA 모델을 이용한 제안된 얼굴 인식 방식이 다양한 자세에서 조명에 대해 보다 신뢰성 있게 동작함을 확인하였다.