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This paper presents a new way for keyword spotting in degraded imaged document. Two prevalent word indexing, OCR and word shape coding, are combined compactly based on the recognition confidence evaluation. The basic procedures are as follows. First, OCR candidates are used for OCR indexing. Second, a new stoke
With large databases of document images available,a method for users to find keywords in documents will be useful. One approach is to perform Optical Character Recognition (OCR) on each document followed by indexing of the resulting text. However, if the quality of the document is poor or time is critical,complete OCR
In this paper, we present a keyword extraction methodology from handwritten Chinese document image based on matching and voting of the local topological structure. In the process, a handwritten keyword image is used as template, from which the local topological structure features of each character pixel are extracted
A critical component of today's commercial search engines is an advertisement platform. The current state-of-the-art of such platforms is primarily based on advanced keyword matching to determine the relevance of advertisements for users' queries. However, such keyword matching techniques suffer from missing user
Inspired by the keyword-based text filter, this paper proposes an image filter which detects the spam image by matching with user-specified image content. In this way, detecting image spam e-mail is converted into image matching process. Stable local feature detection and representation is a fundamental component of
scenes by checking the discovered cross-media correlation. To make these two modalities comparable, photos related to the visited scenic spots are retrieved from image search engines, by the keywords extracted from text-based schedules. Sequences of key frames and retrieved photos are represented as visual word histograms
Overlaid text appears frequently in broadcast sports video. They provide supplementary information regarding the happenings of a particular game. Examples include important events of interest such as bookings and substitutions in a soccer match. Furthermore, overlaid-text is displayed when a particular concept of interest is happening or has happened. This paper presents a technique to automatically...
An approach to image categorization and retrieval based on the combination of visual and semantic features using rough set theory is presented in this paper. We adopt relevance feedback theory to extract the semantic features of images. The decision table is made with the semantic features (keywords) as the condition
Tattoo images on human body have been routinely collected and used in law enforcement to assist in suspect and victim identification. However, the current practice of matching tattoos is based on keywords. Assigning keywords to individual tattoo images is both tedious and subjective. We have developed a content-based
In recent years, medical image fusion is extensively used to help doctors improve the accuracy of medical diagnosis by combining multimodality images acquired under different imaging conditions into a single one. Most of the previous methods aim at attaining information as many as possible from source images. However, some of the exacted information is not necessary or useful for medical diagnosis...
The aim of this research is on developing a dynamic image matching model (DIMM) for smart devices. People with no knowledge on searching keywords can see the information and make good use of it in their daily life. Although existing search engines (Google, Yahoo etc.) have this systems, but it is necessary to get the
Existence of countless digital images has given rise to image retrieval in many applications. Conventional image databases being text-annotated pose two major problems of keywords for images and complexity. Hence, retrieval systems based on image's visual content are more desirable [1]. The content based image
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