• Journal of the Korean Geographical Society
• /
• v.47 no.3
• /
• pp.440-458
• /
• 2012

This study analyzed the ignorance and prejudice with regard to African culture, which can be seen at the textbook and class course centering the geography class from 1990's to the present, and reviewed critically the related education and learning effects for mutual understanding. This study results are as follows: First, in the geographic environment contents, the image regarding huge continent, the local image regarding the various physical environments and the geographical importance as the ancient civilization birthplace were not included in the description. Second, the description regarding the African culture and history was focused to the singular African image, so the fixed concept and distorted image has been rooted into the formation of cultural meta-knowledge. Third, the negative sides rather than positive development and the past backward facts rather than changed status have been emphasized in the description regarding African resources and industry as well, so only the region surrounded with the various problems including poverty and the image as underdeveloped country have been rooted into the description. Now, real Africa view, an image for a variety of attractive and vibrant Africa rather than the same culture and characteristics of African must be learned in text books.

• The KIPS Transactions:PartB
• /
• v.12B no.5 s.101
• /
• pp.527-534
• /
• 2005

Rotation and scale variations make it difficult to solve the problem of shape description and recognition because these variations change the location of points composing the shape. However, some geometric Invariant points and the relations among them are not changed by these variations. Therefore, if points in image space depicted with the r-y coordinates system can be transformed into a new coordinates system that are invariant to rotation and scale, the problem of shape description and recognition becomes easier. This paper presents a shape description method via transformation from the image space into the invariant feature space having two axes: representing relative distance from a centroid and contour segment curvature(CSC). The relative distance describes how far a point departs from the centroid, and the CSC represents the degree of fluctuation in a contour segment. After transformation, mesh features were used to describe the shape mapped onto the feature space. Experimental results show that the proposed method is robust to rotation and scale variations.

• Journal of radiological science and technology
• /
• v.28 no.1
• /
• pp.19-24
• /
• 2005

The purpose of this study was to design and implement a useful annotation-based Radiological image retrieval system to accurately determine on education and image information for Radiological technologists. For better retrieval performance based on large image databases, we presented an indexing technique that integrated $B^+-tree$ proposed by Bayer for indexing simple attributes and inverted file structure for text medical keywords acquired from additional description information about Radiological images. In our results, we implemented proposed retrieval system with Delphi under Windows XP environment. End users, Radiological technologists, are able to store simple attributes information such as doctor name, operator name, body parts, disease and so on, additional text-based description information, and Radiological image itself as well as to retrieve wanted results by using simple attributes and text keywords from large image databases by graphic user interface. Consequently proposed system can be used for effective clinical decision on Radiological image, reduction of education time by organizing the knowledge, and well organized education in the clinical fields. In addition, It can be expected to develop as decision support system by constructing web-based integrated imaging system included general image and special contrast image for the future.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.7
• /
• pp.3756-3777
• /
• 2019

Recent internet development is helping malware researchers to generate malicious code variants through automated tools. Due to this reason, the number of malicious variants is increasing day by day. Consequently, the performance improvement in malware analysis is the critical requirement to stop the rapid expansion of malware. The existing research proved that the similarities among malware variants could be used for detection and family classification. In this paper, a Cross-Platform Malware Variant Classification System (CP-MVCS) proposed that converted malware binary into a grayscale image. Further, malicious features extracted from the grayscale image through Combined SIFT-GIST Malware (CSGM) description. Later, these features used to identify the relevant family of malware variant. CP-MVCS reduced computational time and improved classification accuracy by using CSGM feature description along machine learning classification. The experiment performed on four publically available datasets of Windows OS and Android OS. The experimental results showed that the computation time and malware classification accuracy of CP-MVCS was higher than traditional methods. The evaluation also showed that CP-MVCS was not only differentiated families of malware variants but also identified both malware and benign samples in mix fashion efficiently.

• Journal of Digital Contents Society
• /
• v.17 no.6
• /
• pp.545-553
• /
• 2016

In this study, we propose an information providing and learning system using augmented reality in the exhibition (museum, performance) environment. In a typical exhibition space, a description of a picture or a photograph is provided in a printed matter or a space in the form of an information space (explanatory space), or an auxiliary explanation using an 'audio guide' or a 'docent' program. Augmented reality technology is applied to the exhibition space in the form of a fusion of these methods, and the description of the exhibition is provided to the user in various forms such as text, picture, audio and image, thereby providing stereoscopic information and learning. We apply the augmented reality technology in a specific exhibition space and utilize it as a tool of providing information and learning using image description of pictures.

• Journal of Information Processing Systems
• /
• v.16 no.5
• /
• pp.1083-1094
• /
• 2020

Recognizing plant species based on leaf images is challenging because of the large inter-class variation and inter-class similarities among different plant species. The effective extraction of leaf descriptors constitutes the most important problem in plant leaf recognition. In this paper, a multi-scale angular description method is proposed for fast and accurate leaf recognition and retrieval tasks. The proposed method uses a novel scale-generation rule to develop an angular description of leaf contours. It is parameter-free and can capture leaf features from coarse to fine at multiple scales. A fast Fourier transform is used to make the descriptor compact and is effective in matching samples. Both support vector machine and k-nearest neighbors are used to classify leaves. Leaf recognition and retrieval experiments were conducted on three challenging datasets, namely Swedish leaf, Flavia leaf, and ImageCLEF2012 leaf. The results are evaluated with the widely used standard metrics and compared with several state-of-the-art methods. The results and comparisons show that the proposed method not only requires a low computational time, but also achieves good recognition and retrieval accuracies on challenging datasets.

• Journal of Korea Game Society
• /
• v.3 no.2
• /
• pp.86-92
• /
• 2003

Today, the visual description of body is viewed in various categories, and the circumstance of computers is regarded as new type of communication beyond the circumstance of individual body. In cyber space, when existence and role of character in computer game constitute communication, the ideal body description of each character depicts dramatic beauty, which rises above reality. On this thesis, analyzing the body description and transition on visual in, I grope for a method to utilize in creating game character which is modeled from ideal human being. Although the progress of producing character has already come to limit, concluding that we have to create character model which has marked individuality and beauty by adding modem and future analysis to the golden ratio, which has established since ancient Greece, this paper suggests the method of creating character which has the image of ideal human body.

• Journal of the HCI Society of Korea
• /
• v.2 no.2
• /
• pp.35-43
• /
• 2007

This paper presents a system for image matching and recognition based on image feature detection and description techniques from artificial satellite photographs. We propose some kind of parameters from the varied environmental elements happen by image handling process. The essential point of this experiment is analyzes that affects match rate and recognition accuracy when to change of state of each parameter. The proposed system is basically inspired by Lowe's SIFT(Scale-Invariant Transform Feature) algorithm. The descriptors extracted from local affine invariant regions are saved into database, which are defined by k-means performed on the 128-dimensional descriptor vectors on an artificial satellite photographs from Google earth. And then, a label is attached to each cluster of the feature database and acts as guidance for an appeared building's information in the scene from camera. This experiment shows the various parameters and compares the affected results by changing parameters for the process of image matching and recognition. Finally, the implementation and the experimental results for several requests are shown.

• Journal of Korea Multimedia Society
• /
• v.19 no.8
• /
• pp.1498-1504
• /
• 2016

The progress of mobile computing technology is bringing a large amount of multimedia contents such as image. Thus, we need an image retrieval system which searches semantically relevant image. In this paper, we propose a semantic image annotation and retrieval in mobile environments. Previous mobile-based annotation approaches cannot fully express the semantics of image due to the limitation of current form (i.e., keyword tagging). Our approach allows mobile devices to annotate the image automatically using the context-aware information such as temporal and spatial data. In addition, since we annotate the image using RDF(Resource Description Framework) model, we are able to query SPARQL for semantic image retrieval. Our system implemented in android environment shows that it can more fully represent the semantics of image and retrieve the images semantically comparing with other image annotation systems.

• Journal of Korea Multimedia Society
• /
• v.19 no.2
• /
• pp.138-145
• /
• 2016

LLAH(Locally Likely Arrangement Hashing) is a method which describes image features by exploiting the geometric relationship between their neighbors. Inherently, it is more robust to large view change and poor scene texture than conventional texture-based feature description methods. However, LLAH strongly requires that image features should be detected with high repeatability. The problem is that such requirement is difficult to satisfy in real applications. To alleviate the problem, this paper proposes a method that improves the matching rate of LLAH by exploiting together the brightness of features. Then, it is verified that the matching rate is increased by about 5% in experiments with synthetic images in the presence of Gaussian noise.