• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2008년도 한국컴퓨터종합학술대회논문집 Vol.35 No.1 (A)
• /
• pp.285-286
• /
• 2008

• Journal of Computing Science and Engineering
• /
• 제11권1호
• /
• pp.1-8
• /
• 2017

Naive Bayes nearest neighbor (NBNN) is a simple image classifier based on identifying nearest neighbors. NBNN uses original image descriptors (e.g., SIFTs) without vector quantization for preserving the discriminative power of descriptors and has a powerful generalization characteristic. However, it has a distinct disadvantage. Its memory requirement can be prohibitively high while processing a large amount of data. To deal with this problem, we apply a spherical hashing binary code embedding technique, to compactly encode data without significantly losing classification accuracy. We also propose using an inverted index to identify nearest neighbors among binarized image descriptors. To demonstrate the benefits of our method, we apply our method to two existing NBNN techniques with an image dataset. By using 64 bit length, we are able to reduce memory 16 times with higher runtime performance and no significant loss of classification accuracy. This result is achieved by our compact encoding scheme for image descriptors without losing much information from original image descriptors.

• 정보과학회 논문지
• /
• 제43권8호
• /
• pp.878-882
• /
• 2016

이미지의 내용을 설명하는 캡션을 자동으로 생성하는 기술은 이미지 인식과 자연어처리 기술을 필요로 하는 매우 어려운 기술이지만, 유아 교육이나 이미지 검색, 맹인들을 위한 네비게이션 등에 사용될 수 있는 중요한 기술이다. 본 논문에서는 이미지 캡션 생성을 위해 Convolutional Neural Network(CNN)으로 인코딩된 이미지 정보를 입력으로 갖는 이미지 캡션 생성에 최적화된 Recurrent Neural Network(RNN) 모델을 제안하고, 실험을 통해 본 논문에서 제안한 모델이 Flickr 8K와 Flickr 30K, MS COCO 데이터 셋에서 기존의 연구들보다 높은 성능을 얻음을 보인다.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제26권1호
• /
• pp.150-150
• /
• 1999

In this paper, a content-based image retrieval scheme based on scale-space theory is proposed. The existing methods using scale-space theory consider all scales for image retrieval,thereby requiring a lot of computation. To overcome this problem, the proposed algorithm utilizes amodified histogram intersection method to select candidate images from database. The relative scalebetween a query image and a candidate image is calculated by the ratio of histograms. Feature pointsare extracted from the candidates using a corner detection algorithm. The feature vector for eachfeature point is composed of RGB color components and differential invariants. For computing thesimilarity between a query image and a candidate image, the euclidean distance measure is used. Theproposed image retrieval method has been applied to various images and the performance improvementover the existing methods has been verified.

• Journal of Computing Science and Engineering
• /
• 제8권2호
• /
• pp.65-77
• /
• 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.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (B)
• /
• pp.715-717
• /
• 2004

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on a recursive error back-projection of top-down machine learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes, In addition to, a recursive error back-projection is applied to improve the accuracy of synthesized high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution one captured at a distance.

• 한국정보과학회:학술대회논문집
• /
• 한국정보과학회 2006년도 한국컴퓨터종합학술대회 논문집 Vol.33 No.1 (B)
• /
• pp.193-195
• /
• 2006

As multimedia information increases sharply, In image retrieval field the method that can analyze image data quickly and exactly is required. In the case of image data, because each data includes a lot of informations, between accuracy and speed of retrieval become trade-off. To solve these problem, feature vector extracting process that use Genetic Algorithm for implementing prompt and correct image clustering system in case of retrieval of mass image data is proposed. After extracting color and texture features, the representative feature vector among these features is extracted by using Genetic Algorithm.

• 한국정보과학회논문지:시스템및이론
• /
• 제28권12호
• /
• pp.653-659
• /
• 2001

본 논문에서는 실린더 파노라믹 영상을 생성하기 위한 효율적인 알고리즘을 제시한다. 먼저 영상 정렬 시 실린더와 영상간의 관계를 이용한 영상의 중심으로부터 같은 거리에 있는 영상 스트립을 비교하는 효율적인 영상 정렬 알고리즘을 기술하고, 원과 원에 접하는 다각형간의 관계를 이용하여 이분법으로부터 초점거리를 정확하게 추정하는 방법을 설명한다. 본논문에서 제안하는 알고리즘은 카메라 운동에 대한 제약점은 있지만, 빠르고 간단하기 때문에 실제 응용에서 효과적으로 사용 가능하다.

• 한국초등과학교육학회지:초등과학교육
• /
• 제28권1호
• /
• pp.35-45
• /
• 2009

We analyzed $3^{rd}$ graders' images of scientists and science learning students. We chose $3^{rd}$ graders because this is the time when children first encounter formal science learning opportunities. Draw-A-Scientist-Test (DAST) and the revised Draw-A-Scientist-Test Checklist (DAST-C) were used to analyze students' images of scientists, whereas Drawing-A-Science-Learner- and a checklist were used to analyze students' images of science learning students. We found that $3^{rd}$ graders showed common features of scientists who wore laboratory coats but not wearing glasses, goggles or masks and smiling. While most boys drew a male scientist, about a half of girls drew female scientists. Old and weird looking images of scientists that were typically known in other literatures were not found in this study. Science learning students were not wearing lab coasts, glasses, goggles, nor masks. Most of those students were conducting chemistry related experiments, which seemed to be influenced by the $3^{rd}$ grade's science curriculum. We also found relationships among components of images of scientists and science learning students. Although $3^{rd}$ graders' images of scientists and science learning students showed common features, this typical image was not the same as the previous studies have reported. This implies that the images of scientists and science learning students have not yet fixed by $3^{rd}$ grade. Thus, this seems to be a critical time when children start developing images of scientists. Children's direct experiences in the science classroom along with environmental factors such as media exposures can influence their formation of images of scientists and science learning students.

• 한국정보과학회논문지:소프트웨어및응용
• /
• 제34권9호
• /
• pp.797-803
• /
• 2007

카메라 기반 문서 인식을 위해서는 화질 변화에 적응할 수 있는 이진화 기술이 매우 중요하다. 본 논문에서는 화질 분석을 통해 다양한 화질의 카메라 영상에 효과적으로 적응할 수 있는 이진화 방법을 제안한다. 먼저 이진화 파라미터가 이진화 결과에 미치는 영향을 분석하고, 카메라 영상의 화질을 측정하는 방법을 제안한다. 그리고, 측정된 화질과 이진화 파라미터간의 상관 관계를 통계적으로 분석하여 반영함으로써 화질 변화에 자동으로 적응하는 이진화 방법을 제안한다. 실험을 통해 화질과 이진화 파라미터간에는 유의한 상관 관계가 있으며, 제안하는 방법이 화질에 따라 적절한 파라미터를 추정함으로써 화질변화에 적응함을 확인하였다.