• Title/Summary/Keyword: Photo Retrieval

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A Query-by-Speech Scheme for Photo Albuming (음성 질의 기반 디지털 사진 검색 기법)

  • Kim Tae-Sung;Suh Young-Joo;Lee Yong-Ju;Kim Hoi-Rin
    • MALSORI
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    • no.57
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    • pp.99-112
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    • 2006
  • In this paper, we introduce two retrieval methods for photos with speech documents. We compare the pattern of speech query with those of speech documents recorded in digital cameras, and measure the similarities, and retrieve photos corresponding to the speech documents which have high similarity scores. As the first approach, a phoneme recognition scheme is used as the pre-processor for the pattern matching, and in the second one, the vector quantization (VQ) and the dynamic time warping (DTW) are applied to match the speech query with the documents in signal domain itself. Experimental results show that the performance of the first approach is highly dependent on that of phoneme recognition while the processing time is short. The second method provides a great improvement of performance. While the processing time is longer than that of the first method due to DTW, but we can reduce it by taking approximated methods.

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Visual Location Recognition Using Time-Series Streetview Database (시계열 스트리트뷰 데이터베이스를 이용한 시각적 위치 인식 알고리즘)

  • Park, Chun-Su;Choeh, Joon-Yeon
    • Journal of the Semiconductor & Display Technology
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    • v.18 no.4
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    • pp.57-61
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    • 2019
  • Nowadays, portable digital cameras such as smart phone cameras are being popularly used for entertainment and visual information recording. Given a database of geo-tagged images, a visual location recognition system can determine the place depicted in a query photo. One of the most common visual location recognition approaches is the bag-of-words method where local image features are clustered into visual words. In this paper, we propose a new bag-of-words-based visual location recognition algorithm using time-series streetview database. The proposed algorithm selects only a small subset of image features which will be used in image retrieval process. By reducing the number of features to be used, the proposed algorithm can reduce the memory requirement of the image database and accelerate the retrieval process.

Retrieving of Compositionally Similar Images Using Straight Line Elements (직선 성분을 이용하는 구도가 유사한 사진 검색 방법)

  • Hwang, Joo-Yeon;Lim, Dong-Sup;Paik, Doo-Won
    • Journal of Korea Multimedia Society
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    • v.12 no.11
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    • pp.1539-1546
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    • 2009
  • According to photography, lines are important elements that make composition and mood of photo. In this paper, we proposed a measure for compositional dissimilarity between photos using lines which are basic elements of photography. To identify patterns of lines which classify composition of photos, we investigated both features of compositionally same photos and compositionally different photos. Then we developed effective measure for compositional dissimilarity between photos by applying the investigated features to the measure, and we implemented an image searching system which retrieves photo compositionally similar to given query to evaluate performance of proposed method. The searching system showed the precision of about 85% maximally for the highly matched 10 results and was capable of reliably retrieving compositionally similar to given query even if some objects were included in photos.

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Adaptive Event Clustering for Personalized Photo Browsing (사진 사용 이력을 이용한 이벤트 클러스터링 알고리즘)

  • Kim, Kee-Eung;Park, Tae-Suh;Park, Min-Kyu;Lee, Yong-Beom;Kim, Yeun-Bae;Kim, Sang-Ryong
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.711-716
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    • 2006
  • Since the introduction of digital camera to the mass market, the number of digital photos owned by an individual is growing at an alarming rate. This phenomenon naturally leads to the issues of difficulties while searching and browsing in the personal digital photo archive. Traditional approach typically involves content-based image retrieval using computer vision algorithms. However, due to the performance limitations of these algorithms, at least on the casual digital photos taken by non-professional photographers, more recent approaches are centered on time-based clustering algorithms, analyzing the shot times of photos. These time-based clustering algorithms are based on the insight that when these photos are clustered according to the shot-time similarity, we have "event clusters" that will help the user browse through her photo archive. It is also reported that one of the remaining problems with the time-based approach is that people perceive events in different scales. In this paper, we present an adaptive time-based clustering algorithm that exploits the usage history of digital photos in order to infer the user's preference on the event granularity. Experiments show significant performance improvements in the clustering accuracy.

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Visual Media Service Retrieval Using ASN.1-based Ontology Reasoning (ASN.1 기반의 온톨로지 추론을 이용한 시각 미디어 서비스 검색)

  • Min, Young-Kun;Lee, Bog-Ju
    • The KIPS Transactions:PartB
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    • v.12B no.7 s.103
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    • pp.803-810
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    • 2005
  • Information retrieval is one of the most challenging areas in which the ontology technology is effectively used. Among them image retrieval using the image meta data and ontology is the one that can substitute the keyword-based image retrieval. In the paper, the retrieval of visual media such as the art image and photo picture is handled. It is assumed that there are more than one service providers of the visual media and also there is one central service broker that mediates the user's query. Given the user's query the first step that must be done in the service broker is to get the list of candidate service providers that fit the query. This is done by defining various ontologies such as the service ontology and matching the query against the ontology and providers. A novel matching method based on the ASN.1. The experiment shows that the method is more effective than existing tree-based and interval-based methods. Ontology merging issue is also handled that can happen when the service providers register their service into the service broker. An effective method is also proposed.

Comparison and Evaluation of Web-based Image Search Engines (이미지정보 탐색을 위한 웹 검색엔진의 비교 평가)

  • Kim, Hyo-Jung
    • Journal of Information Management
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    • v.31 no.4
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    • pp.50-70
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    • 2000
  • Since the contents of internet resources are beginning to include texts, images and sounds, different Web-based image search engines have been developed accordingly. It is a fact that these diversities of multimedia contents have made search process and retrieval of relevant information very difficult. The purpose of the study is to compare and evaluate its special features and performance of the existing image search engines in order to provide user help to select appropriate search engines. The study selected AV Photo Finder, Lycos MultiMedia, Amazing Picture Machine, Image Surfer, WebSeek, Ditto for comparison and evaluation because of their reputations of popularity among users of image search engines. The methodology of the study was to analyze previous related literature and establish criteria for the evaluation of image search engines. The study investigated characteristics, indexing methods, search capabilities, screen display and user interfaces of different search engines for the purpose of comparison of its performance. Finally, the study measured relative recall and precision ratios to evaluate their electiveness of retrieval under the experimental set up. Results of the comparative analysis in regard to its search performance are as follows. AV Photo Finder marked the highest rank among other image search engines. Ditto and WebSeek also showed comparatively high precision ratio. Lycos MultiMedia and Image Surfer follows after them. Amazing Picture Machine stowed the lowest in ranking.

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Image Retrieval Using the Fusion of Spatial Histogram and wavelet Moments (공간 히스토그램과 웨이브렛 모멘트의 융합에 의한 영상 검색)

  • Seo, Sang Yong;Kim, Nam Cheol
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.38 no.4
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    • pp.110-110
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    • 2001
  • 본 논문에서는 공간 히스토그램과 웨이브렛 모멘트를 융합하여 검색 효율을 크게 향상시키는 방법을 제안한다. 이 방법에서는 질의영상과 DB영상간의 유사도를 구할 때 히스토그램의 유사도와 웨이브렛 모멘트의 유사도를 효과적으로 융합한다. 즉, 공간적 이동, 회전 등에 강한 히스토그램 특징과 주파수 대역별로 구해지는 웨이브렛 모멘트 특징을 잘 융합함으로써 검색성능의 향상을 추구한다. 제안한 방법의 성능을 평가하기 위한 시험영상 DB로는 Brodatz 질간 영상 DB와 Corel Draw Photo 영상 DB를 사용하였다. 실험 결과, 제안한 방법으로 구한 검색율이 Brodatz DB에서 히스토그램이나 웨이브렛 모멘트만으로 구한 검색율보다 각각 5.3%와 13.8% 향상되었고, Corel Draw Photo DB에서는 각각 15.5%와 3.2% 향상됨을 확인할 수 있었다.

PhotoToc: an Implementation of a Ranking System by using User Favor-Based Metrics (포토톡 : 사용자 선호 기반 멀티미디어 콘텐츠 랭킹 시스템의 구현)

  • Lee, Jin-Soo;Park, Al-Eum;Choi, Song-Ah;Ahn, Hoo-Young;Park, Young-Ho
    • Journal of Digital Contents Society
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    • v.8 no.2
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    • pp.113-119
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    • 2007
  • Recently, multimedia applications using internet are increasing by emergency of UCC. The retrieval of photo, video, audio is a main issue to increase utility of access and efficiency of access time. But the exist multimedia applications do not provide the practical ranking system. They provide only simple ranking system using metric. This paper provides "PhotoToc", the user favor-based multimedia ranking system, that can provide differenced view to users. The proposed system has a to retrieve the user centered results.

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A Categorization Scheme of Tag-based Folksonomy Images for Efficient Image Retrieval (효과적인 이미지 검색을 위한 태그 기반의 폭소노미 이미지 카테고리화 기법)

  • Ha, Eunji;Kim, Yongsung;Hwang, Eenjun
    • KIISE Transactions on Computing Practices
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    • v.22 no.6
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    • pp.290-295
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    • 2016
  • Recently, folksonomy-based image-sharing sites where users cooperatively make and utilize tags of image annotation have been gaining popularity. Typically, these sites retrieve images for a user request using simple text-based matching and display retrieved images in the form of photo stream. However, these tags are personal and subjective and images are not categorized, which results in poor retrieval accuracy and low user satisfaction. In this paper, we propose a categorization scheme for folksonomy images which can improve the retrieval accuracy in the tag-based image retrieval systems. Consequently, images are classified by the semantic similarity using text-information and image-information generated on the folksonomy. To evaluate the performance of our proposed scheme, we collect folksonomy images and categorize them using text features and image features. And then, we compare its retrieval accuracy with that of existing systems.

Web-based Image Retrieval and Classification System using Sketch Query (스케치 질의를 통한 웹기반 영상 검색과 분류 시스템)

  • 이상봉;고병철;변혜란
    • Journal of KIISE:Software and Applications
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    • v.30 no.7_8
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    • pp.703-712
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    • 2003
  • With the explosive growth n the numbers and sizes of imaging technologies, Content-Based Image Retrieval (CBIR) has been attacked the interests of researchers in the fields of digital libraries, image processing, and database systems. In general, in the case of query-by-image, in user has to select an image from database to query, even though it is not his completely desired one. However, since query-by-sketch approach draws a query shape according to the user´s desire it can provide more high-level searching interface to the user compared to the query-b-image. As a result, query-by-sketch has been widely used. In this paper, we propose a Java-based image retrieval system that consists of sketch query and image classification. We use two features such as color histogram and Haar wavelets coefficients to search similar images. Then the Leave-One-Out method is used to classify database images. The categories of classification are photo & painting, city & nature, and sub-classification of nature image. By using the sketch query and image classification, w can offer convenient image retrieval interface to user and we can also reduce the searching time.