• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권7호
• /
• pp.2997-3017
• /
• 2020

With the advancement in the field of image processing, images are being processed using various image processing algorithms. Nowadays, many efficient content-aware image resizing techniques are being used to safeguard the prominent regions and to generate better results that are visually appealing and pleasing while resizing. Advancements in the new display device with varying screen size demands the development of efficient image resizing algorithm. This paper presents a survey on various image retargeting methods, comparison of image retargeting results based on performance, and also exposes the main challenges in image retargeting such as content preservation of important regions, distortion minimization, and improving the efficiency of image retargeting methods. After reviewing literature from researchers it is suggested that the use of the single operator in image retargeting such as scaling, cropping, seam carving, and warping is not sufficient for obtaining satisfactory results, hence it is essential to combine multiple image retargeting operators. This survey is useful for the researchers interested in content-aware image retargeting.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제7권12호
• /
• pp.3149-3165
• /
• 2013

Content based image retrieval is increasingly gaining popularity among image repository systems as images are a big source of digital communication and information sharing. Identification of image content is done through feature extraction which is the key operation for a successful content based image retrieval system. In this paper content based image retrieval system has been developed by adopting a strategy of combining multiple features of shape, color and relevance feedback. Shape is served as a primary operation to identify images whereas color and relevance feedback have been used as supporting features to make the system more efficient and accurate. Shape features are estimated through second derivative, least square polynomial and shapes coding methods. Color is estimated through max-min mean of neighborhood intensities. A new technique has been introduced for relevance feedback without bothering the user.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
• /
• pp.35-38
• /
• 2000

The method of Content-based Triangular Mesh Image representation in moving pictures makes better performance in prediction error ratio and visual efficiency than that of classical block matching. Specially if background and objects can be separated from image, the objects are designed by Irregular mesh. In this case this irregular mesh design has an advantage of increasing video coding efficiency. This paper presents the techniques of mesh generation, motion estimation using these mesh, uses image warping transform such as Affine transform for image reconstruction, and evaluates the content based mesh design through computer simulation.

• 한국콘텐츠학회논문지
• /
• 제12권4호
• /
• pp.186-197
• /
• 2012

본 논문은 영상콘텐츠에서 공간콘텐츠로의 전환의 핵심을 각색(adaptation)에 두고, 테마공간의 원형콘텐츠인 영상콘텐츠가 어떻게 각색되어 공간으로 재현되어야 하는가를 밝히는 것을 목적으로 한다. 또한 스토리텔링에 대한 연구는 무수히 많이 쏟아져 나오고 있고, 소설의 영화화나 TV드라마화, 영화의 게임화나 그 반대와 관련한 각색 연구는 많지만 영상콘텐츠에서 테마공간으로 전환 시의 각색의 방법과 스토리텔링의 전단계라는 측면에서의 각색에 대한 연구는 부족한 편이다. 우선 각색의 정의를 내리고, 자네티와 더들리의 각색방법을 차용하여 영상콘텐츠의 테마공간화에 적용해 보았다. 이어서 테마공간의 특징을 살펴본 후 테마공간은 결국 영상콘텐츠의 이야기 이미지 행위의 재현 장소임을 사례분석과 함께 밝히고, 각각 어떤 각색을 통해 재현되고 있는가를 분석하였다. 연구결과 공간의 스토리텔링보다 각색이 선행작업이어야 하고, 3인칭 시점의 영상콘텐츠와는 달리 1인칭 시점의 테마공간 재현의 핵심은 관람이 아닌 체험임을 확인하였다. 따라서 본 논문에서는 영상콘텐츠에서 테마공간의 전환은 단순한 모방이 아니라 새로운 콘텐츠로 재창조되었음을 밝혔다. 향후 다양한 테마공간의 구체적인 각론적 층위에서의 분석을 통해 양자간의 전환이 효과적으로 작용하고, 다양한 각색 방법이 실질적으로 적용되기를 기대한다.

• 반도체디스플레이기술학회지
• /
• 제6권2호
• /
• pp.53-57
• /
• 2007

In this paper, a new content-based color image retrieval method is proposed, in which both the color content and the spatial relationship of image have been taken into account. In order to represent the spatial distribution information of image, a disorder matrix, which has the invariance to the rotation and translation of the image content, has been designed. This is based on multi-resolution color-spatial information. We present our algorithm in the following section, and then verified the search results with comparison to other methods, such as color histogram, wavelet histogram, correlogram and wavelet correlogram. Experimental results with various types of images show that the proposed method not only achieves a high image retrieval performance but also improve the retrieval precision.

• International Journal of Contents
• /
• 제10권3호
• /
• pp.9-16
• /
• 2014

Depth-image-based rendering is generally used in real-time 2D-to-3D conversion for 3DTV. However, inaccurate depth maps cause flickering issues between image frames in a video sequence, resulting in eye fatigue while viewing 3DTV. To resolve this flickering issue, we propose a new 2D-to-3D conversion scheme based on fast and robust depth-map generation from a 2D video sequence. The proposed depth-map generation algorithm divides an input video sequence into several cuts using a color histogram. The initial depth of each cut is assigned based on a hypothesized depth-gradient model. The initial depth map of the current frame is refined using color and motion information. Thereafter, the depth map of the next frame is updated using the difference image to reduce depth flickering. The experimental results confirm that the proposed scheme performs real-time 2D-to-3D conversions effectively and reduces human eye fatigue.

• ETRI Journal
• /
• 제38권1호
• /
• pp.174-184
• /
• 2016

Information identification with image data by means of low-level visual features has evolved as a challenging research domain. Conventional text-based mapping of image data has been gradually replaced by content-based techniques of image identification. Feature extraction from image content plays a crucial role in facilitating content-based detection processes. In this paper, the authors have proposed four different techniques for multiview feature extraction from images. The efficiency of extracted feature vectors for content-based image classification and retrieval is evaluated by means of fusion-based and data standardization-based techniques. It is observed that the latter surpasses the former. The proposed methods outclass state-of-the-art techniques for content-based image identification and show an average increase in precision of 17.71% and 22.78% for classification and retrieval, respectively. Three public datasets - Wang; Oliva and Torralba (OT-Scene); and Corel - are used for verification purposes. The research findings are statistically validated by conducting a paired t-test.

• ETRI Journal
• /
• 제20권3호
• /
• pp.272-283
• /
• 1998

In this paper, we propose efficient content-based image retrieval methods using the automatic extraction of the low-level visual features as image content. Two new feature extraction methods are presented. The first one os an advanced color feature extraction derived from the modification of Stricker's method. The second one is a texture feature extraction using some DCT coefficients which represent some dominant directions and gray level variations of the image. In the experiment with an image database of 200 natural images, the proposed methods show higher performance than other methods. They can be combined into an efficient hierarchical retrieval method.

• 산업경영시스템학회지
• /
• 제27권3호
• /
• pp.59-65
• /
• 2004

This paper explores an image segmentation and representation method using Vector Quantization(VQ) on color and texture for content-based image retrieval system. The basic idea is a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. These schemes are used for object-based image retrieval. Features for image retrieval are three color features from HSV color model and five texture features from Gray-level co-occurrence matrices. Once the feature extraction scheme is performed in the image, 8-dimensional feature vectors represent each pixel in the image. VQ algorithm is used to cluster each pixel data into groups. A representative feature table based on the dominant groups is obtained and used to retrieve similar images according to object within the image. The proposed method can retrieve similar images even in the case that the objects are translated, scaled, and rotated.

• Journal of information and communication convergence engineering
• /
• 제19권1호
• /
• pp.36-41
• /
• 2021

Text-based image retrieval is not only cumbersome as it requires the manual input of keywords by the user, but is also limited in the semantic approach of keywords. However, content-based image retrieval enables visual processing by a computer to solve the problems of text retrieval more fundamentally. Vision applications such as extraction and mapping of image characteristics, require the processing of a large amount of data in a mobile environment, rendering efficient power consumption difficult. Hence, an effective image retrieval method on mobile platforms is proposed herein. To provide the visual meaning of keywords to be inserted into images, the efficiency of image retrieval is improved by extracting keywords of exchangeable image file format metadata from images retrieved through a content-based similar image retrieval method and then adding automatic keywords to images captured on mobile devices. Additionally, users can manually add or modify keywords to the image metadata.