• Journal of Institute of Control, Robotics and Systems
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• v.14 no.5
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• pp.473-482
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• 2008

In this paper we propose an expert system for content-based image retrieval with object database. The proposed system finds keyword by using knowledge-base and feature of extracted object, and retrieves image by using keyword based image retrieval method. The system can decrease error of image retrieval and save running time. The system also checks whether similar objects exist or not. If not, user can store information of object in object database. Proposed system is flexible and extensible, enabling experts to incrementally add more knowledge and information. Experimental results show that the proposed system is more effective than existing content-based image retrieval method in running time and precision.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.6
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• pp.455-461
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• 2002

Object-based image retrieval method is addressed. A new image segmentation algorithm and image comparing method between segmented objects are proposed. For image segmentation, color and texture features are extracted from each pixel in the image. These features we used as inputs into VQ (Vector Quantization) clustering method, which yields homogeneous objects in terns of color and texture. In this procedure, colors are quantized into a few dominant colors for simple representation and efficient retrieval. In retrieval case, two comparing schemes are proposed. Comparing between one query object and multi objects of a database image and comparing between multi query objects and multi objects of a database image are proposed. For fast retrieval, dominant object colors are key-indexed into database.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.426-429
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• 1999

Many similar class components are stored in object-storage but the object-storage has needed the retrieval function of correct component for reuse. Accordingly this paper designed the class component retrieval viewer of the object-storage by using the improved spreading activation strategy. Object-storage has made up of information of inheritance relation, superclass, subclass, and we defined the queries about each class function. Also we specified connectionist relaxation of the each class and query, finally we gained retrieval result which showed highest activation value order of class component information including the query function.

• Journal of Korea Multimedia Society
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• v.6 no.2
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• pp.240-246
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• 2003

In this paper, we propose the fast image retrieval method based on object regions using bidirectional round filter in the wavelet transform region. A conventional method that extracts feature vectors on the whole of subband is reduced retrieval efficiency, because of unnecessary background information. The proposed method that extracts feature vectors on the only object region of subband by using bidirectional round filter improve retrieval efficiency, because of removing of background information. And it certainly maintains retrieval efficiency in case of reduction of feature vectors according to color information. Consequently, the retrieval efficiency is improved with 2.5%∼5.3% values, which have a little changes according to characteristics of image.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.453-456
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• 2003

Compared with other features of the image, color features are less sensitive to noise and background complication. Besides, this adding to object segmentation has more accuracy of image retrieval. This paper presents object segmentation and HAQ(Histogram Analysis and Quantization) algorithm approach to extract features(the object information and the characteristic colors) of an image. The empirical results shows that this method presents exactly spatial and color information of an image as image retrieval's feature.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.33-43
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• 2020

Retrieving a 3D model from a 3D database and augmenting the retrieved model in the Augmented Reality system simultaneously became an issue in developing the plausible AR environments in a convenient fashion. It is considered that the sketch-based 3D object retrieval is an intuitive way for searching 3D objects based on human-drawn sketches as query. In this paper, we propose a novel deep learning based approach of retrieving a sketch-based 3D object as for an Augmented Reality Model. For this work, we introduce a new method which uses Sketch CNN, Wasserstein CNN and Wasserstein center loss for retrieving a sketch-based 3D object. Especially, Wasserstein center loss is used for learning the center of each object category and reducing the Wasserstein distance between center and features of the same category. The proposed 3D object retrieval and augmentation consist of three major steps as follows. Firstly, Wasserstein CNN extracts 2D images taken from various directions of 3D object using CNN, and extracts features of 3D data by computing the Wasserstein barycenters of features of each image. Secondly, the features of the sketch are extracted using a separate Sketch CNN. Finally, we adopt sketch-based object matching method to localize the natural marker of the images to register a 3D virtual object in AR system. Using the detected marker, the retrieved 3D virtual object is augmented in AR system automatically. By the experiments, we prove that the proposed method is efficiency for retrieving and augmenting objects.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.778-781
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• 2015

The paper presents a new way of visual descriptor for deformable object retrieval on the basis of partition based description. The proposed descriptor technology partitions a given object into boundary area and interior area and extracts a descriptor from each area. The final descriptor combines these descriptors. From a given image, deformable object is segmented. The center position of the deformable object is calculated. The object is partitioned into N × N blocks on the basis of the given center position. Blocks are classified as boundary area and interior area depending on the pixels in the block. The proposed descriptor consists of extracted MPEG-7 dominant descriptors from both the boundary and interior area. The performance of proposed method is tested on a database of 1,973 handbag images constructed with view point changes. ARR (Average Retrieval Rate) is used for the retrieval accuracy of the proposed algorithm, compared with MPEG-7 dominant color descriptor.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.27-33
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• 2006

In this thesis, we presents the component design and retrieval prototype system which can retrieve the most appropriate component for reuse system. If it used only an abject to reuse unit, it can not understand mutual reaction and can not sustain relationship between objects. Therefore, we porposed clustering component for reuse unit. It makes to understand relationship and reaction between object, so User can retrieve the proper component for reuse system. And porposed retrieval prototype system can select the correct things. it provide 3 facet retrieval environment against ambiguous retrieval definition.

• Journal of Computing Science and Engineering
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• v.8 no.2
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• pp.65-77
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• 2014

To address the problem of multi-target retrieval (MTR) of remote sensing images, this study proposes a new object-level feature representation model. The model provides an enhanced application image representation that improves the efficiency of MTR. Generating the model in our scheme includes processes, such as object-oriented image segmentation, feature parameter calculation, and symbolic image database construction. The proposed model uses the spatial representation method of the extended nine-direction lower-triangular (9DLT) matrix to combine spatial relationships among objects, and organizes the image features according to MPEG-7 standards. A similarity metric method is proposed that improves the precision of similarity retrieval. Our method provides a trade-off strategy that supports flexible matching on the target features, or the spatial relationship between the query target and the image database. We implement this retrieval framework on a dataset of remote sensing images. Experimental results show that the proposed model achieves competitive and high-retrieval precision.

• Biomolecules & Therapeutics
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• v.16 no.3
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• pp.173-178
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• 2008

Several lines of evidence indicate that scopolamine as a nonselective muscarinic antagonist disrupts object recognition performance and spatial working memory when administered systemically. In the present study, we investigated the different effects of scopolamine on acquisition, consolidation, and retrieval phases of object recognition performance and spatial working memory using the object recognition and the Morris water maze tasks in mice. In the acquisition phase test, scopolamine decreased recognition index on object recognition task and the trial 1 to trial 2 differences on Morris water maze task. In the consolidation and retrieval phase tests, scopolamine also decreased recognition index on object recognition task, where as scopolamine did not exhibited any effects on the Morris water maze task.