http://semanticmetadata.net/wiki/ 2012-05-17T21:16:10-05:00 http://semanticmetadata.net/wiki/ http://semanticmetadata.net/wiki/lib/tpl/default/images/favicon.ico text/html 2012-03-08T03:43:40-05:00 mlux http://semanticmetadata.net/wiki/doku.php?id=lire:imageread&rev=1331199820&do=diff Java is unfortunately limited in it's ability to handle images. But there are two basic workarounds. * You can convert all images to a format that Java can handle. Just use ImageMagick or some other great tool to batch process yout images and convert them all to RGB color JPEGs. This is a non Java approach and definitely the faster one. * You can circumvent the ImageIO.read(..) metzhod by using ImageJ. In ImageJ you've got the ImagePlus class, which supprts loading and decoding of various f… text/html 2012-03-08T03:17:31-05:00 mlux http://semanticmetadata.net/wiki/doku.php?id=start&rev=1331198251&do=diff Welcome to the Wiki of SemanticMetadata.net. Within this Wiki you will find a lot of documentation on Lire as well as Caliph and Emir. Please note that I had to remove editing capabilities as this wiki was spammed and I had to remove the spam manually. If you have any suggestions or if you want to add text please contact me. text/html 2011-10-27T04:10:19-05:00 mlux http://semanticmetadata.net/wiki/doku.php?id=lire:manydocs&rev=1319706619&do=diff Lire has the ability to create indexes with lots of different features (descriptors, like RGB color histograms or CEDD). While this opens the opportunity to flexibility at search time as we can select the feature at the time we create a query, the index tends to get bigger and bigger and searcher take longer and longer. text/html 2011-10-24T07:49:39-05:00 mlux http://semanticmetadata.net/wiki/doku.php?id=lire:lire&rev=1319460579&do=diff The LIRE (Lucene Image REtrieval) library a simple way to create a Lucene index of image features for content based image retrieval (CBIR). The implemented features are * ScalableColor, ColorLayout and EdgeHistogram (MPEG-7) * CEDD and FCTH (contributed by Savvas Chatzichristofis) * Color histograms (HSV and RGB), Tamura & Gabor, auto color correlogram, JPEG coefficient histogram (common global descriptors) * Visual words based on SIFT and SURF text/html 2011-10-20T07:19:09-05:00 mlux http://semanticmetadata.net/wiki/doku.php?id=lire:bovw&rev=1319113149&do=diff Lire supports creation of a bag of visual words index and search within. You need to index documents the traditional way first and you have to take care of creating the right local features. This basically means that you'll need to use the SurfDocumentBuilder to get the local features for later BoVW indexing based on SURF features. text/html 2011-07-30T13:38:04-05:00 http://semanticmetadata.net/wiki/doku.php?id=lire:lirefaq&rev=1312051084&do=diff If you can't find any answer to your questions please drop a mail to mathias and he will (a) answer your question and (b) put it in the FAQ. Spam approved email visualization see below ;) What can Lire do for me? Lire is the right choice if you want to search in a repository of raster images (ditial photos, jpegs, pngs ...) for similar images. It provides an easy way to (i) create an index for your images and (ii) search the index. text/html 2011-07-26T14:24:31-05:00 http://semanticmetadata.net/wiki/doku.php?id=lire:createindex&rev=1311708271&do=diff Use the DocumentBuilderFactory to create a DocumentBuilder, for instance with DocumentBuilderFactory.getExtensiveDocumentBuilder(). Add images to an index using following steps: * With this DocumentBuilder Lucene documents can be created from images, for instance with builder.createDocument(FileInputStream, String). * Eventually enrich the documents with your own data. * Add the document to an index. text/html 2011-07-25T16:33:45-05:00 http://semanticmetadata.net/wiki/doku.php?id=wiki_editing_title&rev=1311629625&do=diff wiki editing content