Dr. Dobb's Journal - October 2008 - (Page 53)

d10NG_p4db 8/14/08 3:12 PM Page 53 As Figure 1 illustrates, the ImageSearcher application is made up of six main classes: • • • • • • ImageSearcherForm ImageDialog ImageViewer ThumbnailController ThumbnailImageEventHandler BuildIndex Figure 1: ImageSearcher classes and their relationships. ImageSearcherForm is the main point of entry into the application. It lets users enter the directory where the images are stored, where the index directory is to be created, and what search parameters (start and end dates, user comments, and so on) to use. The remaining classes control the display of the thumbnail images in the status window. This portion makes extensive reuse of code from Lieven’s Image Thumbnail Viewer. The BuildIndex class is where the index creation and searching takes place. To use Lucene, I first create an index by instantiating an IndexWriter(). An IndexWriter is created using the following constructor: IndexWriter idxWriter = new IndexWriter(indexDir, new StandardAnalyzer(), true); where indexDir represents the path to the index directory. Text is analyzed with the StandardAnalyzer; the last argument is a Boolean variable that, if set to True, creates the index or overwrites the existing one. If set to False, it appends to the existing index. Analyzers in Lucene can be used to tokenize text, extract relevant words, remove common words, stem the words (that is, reduce them to the root form; for example, “edits,” “editor,” and “editing” are condensed to “edit”), and perform any other processing before storing it into the index. The common analyzers provided by Lucene are: • WhiteSpaceAnalyzer, which separates tokens based on whitespace. • SimpleAnalyzer, which tokenizes the string to a set of words and converts them to lowercase. • StandardAnalyzer, which tokenizes the string to a set of words identifying acronyms, e-mail addresses, host names, and so on, discarding the basic English stop words (a, an, the, to) and stemming the words. A Lucene index is a sequence of files. All searching is done on this index. The raw EXIF metadata associated with the image files has to be read and extracted from my image files, and passed to Lucene where it can be indexed and searched. The IndexWriter object is created in the BuildIndex constructor, which takes in two arguments; the first is the directory containing your image files, the second is the directory in which the index files are created. Next, the IndexDocs() method is called. This method has one argument, which is the name of the directory containing your image files. It runs through each file in the specified directory, checks that it is a JPEG file, and creates an Image object from the file, using the call Image.FromFile(filename) from the System.Drawing package: Image img = Image.FromFile(file) Figure 2: ImageSearcher application startup screen. The aforementioned EXIF tags are extracted from each image file. For each image file processed, a Document() object is created. This is created using the Document constructor as follows: Document d = new Document(); Next, the ExifExtractor library is used to extract EXIF information from the image files. To keep the application simple, I extract only “Date Time” and “User Comment” EXIF data. EXIF data is extracted as follows: First, create the EXIFExtractor instance, Goheer.EXIF.EXIFextractor er = new Goheer.EXIF. EXIFextractor(ref img, "\n"); Next, retrieve Date/Time EXIF data: string s1 = (String)er["Date Time"]; Likewise, to extract the user comments EXIF information, we access the er object as follows: string s2 = (String)er["User Comment"]; Documents are the primary retrievable items from a Lucene query. Each Document object is made up of one or more field objects. Fields represent a section of the Document. They contain the name of the section and actual data associated with the section. Each field contains information that you query against or display in your search results. Because I will be using the filename, date, and time the picture was taken and user comments in the search results, these keywords would be added to the Document object as a field. Each of these keywords has an associated value. These values are the EXIF data extracted from the image file. Field values are a sequence of terms. I construct the Field object using the constructor: October 2008 l www.ddj.com l Dr. Dobb’s Journal 53 http://www.ddj.com

Table of Contents Feed for the Digital Edition of Dr. Dobb's Journal - October 2008

Dr. Dobb's Journal - October 2008 Contents Friday Night Fish Fry Alia Vox Developer Diaries Developer’s Notebook Is Your Next Language COBOL? Conversations Safe Coding Practices Code Signing in Adobe AIR OpenID Single Sign-On The Book Cipher Algorithm Indexing and Searching Image files Extending Continuous Integration Into ALM The Agile Edge Effective Concurrency Swaine’s Flames

Dr. Dobb's Journal - October 2008

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