Konstantinos Zagoris

Image retrieval systems based on compact shape descriptor and relevance feedback information

One of the most important and most used low-level image feature is the shape employed in a variety of systems such as document image retrieval through word spotting. In this paper an MPEG-like descriptor is proposed that contains conventional contour and region shape features with a wide applicability from any arbitrary shape to document retrieval through word spotting. Its size and storage requirements are kept to minimum without limiting its discriminating ability. In addition to that, a relevance feedback technique based on Support Vector Machines is provided that employs the proposed descriptor with the purpose to measure how well it performs with it. In order to evaluate the proposed descriptor it is compared against different descriptors at the MPEG-7 CE1 Set B database.

A Document Image Retrieval System

In this paper, a system is presented that locates words in document image archives. This technique performs the word matching directly in the document images bypassing character recognition and using word images as queries. First, it makes use of document image processing techniques, in order to extract powerful features for the description of the word images. The features used for the comparison are capable of capturing the general shape of the query, and escape details due to noise or different fonts. In order to demonstrate the effectiveness of our system, we used a collection of noisy documents and we compared our results with those of a commercial optical character recognition (OCR) package.

img(Anaktisi): A Web Content Based Image Retrieval System

img(Anaktisi) is a C#/.NET content base image retrieval application suitable for the web. It provides ef¿cient retrieval services for various image databases using as a query a sample image, an image sketched by the user and keywords. The image retrieval engine is powered by innovative compact and effective descriptors. Also, an Auto Relevance Feedback (ARF) technique is provided to the user. This technique readjusts the initial retrieval results based on user preferences improving the retrieval score signi¿cantly. img(Anaktisi) can be found at http://www.anaktisi.net

ICFHR 2014 Competition on Handwritten Keyword Spotting (H-KWS 2014)

H-KWS 2014 is the Handwritten Keyword Spotting Competition organized in conjunction with ICFHR 2014 conference. The main objective of the competition is to record current advances in keyword spotting algorithms using established performance evaluation measures frequently encountered in the information retrieval literature. The competition comprises two distinct tracks, namely, a segmentation-based and a segmentation-free track. Five (5) distinct research groups have participated in the competition with three (3) methods for the segmentation-based track and four (4) methods for the segmentation-free track. The benchmarking datasets that were used in the contest contain both historical and modern documents from multiple writers. In this paper, the contest details are reported including the evaluation measures and the performance of the submitted methods along with a short description of each method.

Automatic Image Annotation and Retrieval Using the Joint Composite Descriptor

Capable tools are needed in order to successfully search and retrieve a suitable image from large image collections. Many content-based image retrieval systems employ low-level image features such as color, texture and shape in order to locate the image. Although the above approaches are successful, they lack the ability to include human perception in the query for retrieval because the query must be an image. In this paper a new image annotation technique and a keyword-based image retrieval system are presented, which map the low-level features of the Joint Composite Descriptor to the high-level features constituted by a set of keywords. One set consists of colors-keywords and the other set consists of words. Experiments were performed to demonstrate the effectiveness of the proposed technique.

Web Document Image Retrieval System Based on Word Spotting

Nowadays, the huge non-indexing quantities of image archives (especially document images) require the development of intelligent tools for their retrieval with convenience comparable of the texts search engines. The proposed technique addresses the document retrieval problem by a word matching procedure. It performs matching directly in the images bypassing OCR and using word-images as queries. It is constituted of two different parts: The offline and the online operation. In the offline operation, the archive of document images is examined and the results are stored in a database. The online operation consists of the Web interface, the creation of the words image and finally, the matching stage. The proposed matching process it can be described shortly as a two-threshold rating system. Finally, the proposed system has been build and it can be found in at the Web address: http://orpheus.ee.duth.gr/irs2.

Computer-aided diagnosis of mammographic masses based on a supervised content-based image retrieval approach

Abstract In this work, the incorporation of content-based image retrieval (CBIR) into computer aided diagnosis (CADx) is investigated, in order to contribute to the decision-making process of radiologists in the characterization of mammographic masses. The proposed scheme comprises two stages: A margin-specific supervised CBIR stage that retrieves images from reference cases along with a decision stage that is based on the retrieved items. The feature set utilized exploits state-of-the-art features along with a newly proposed texture descriptor, namely mHOG, targeted to capturing margin and core specific mass properties. Performance evaluation considers the CBIR and diagnosis stages separately and is addressed by using standard measures on an enhanced version of the widely adopted digital database for screening mammography (DDSM). The proposed scheme achieved improved performance of CADx of masses in X-ray mammography experimentally compared to the state-of-the-art.

www.MMRetrieval.net: a multimodal search engine

We introduce an experimental search engine for multilingual and multimedia information, employing a holistic web interface and enabling the use of highly distributed indices. Modalities are searched in parallel, and results can be fused via several selectable methods. The engine also provides multistage retrieval, as well as a single text index baseline for comparison purposes. Initial impressions on its effectiveness are positive, while its efficiency may easily be improved.

ICFHR2016 Handwritten Document Image Binarization Contest (H-DIBCO 2016)

H-DIBCO 2016 is the international Handwritten Document Image Binarization Contest organized in the context of ICFHR 2016 conference. The general objective of the contest is to identify current advances in document image binarization of handwritten document images using performance evaluation measures that are motivated by document image analysis and recognition requirements. This paper describes the contest details including the evaluation measures used as well as the performance of the 12 submitted methods along with a brief description of each method.

Segmentation-Based Historical Handwritten Word Spotting Using Document-Specific Local Features

Many word spotting strategies for the modern documents are not directly applicable to historical handwritten documents due to writing styles variety and intense degradation. In this paper, a new method that permits effective word spotting in handwritten documents is presented that relies upon document-specific local features which take into account texture information around representative key points. Experimental work on two historical handwritten datasets using standard evaluation measures shows the improved performance achieved by the proposed methodology.