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Image Search

Image Search. Implementation Results Ken Schmidt. Some Implementation Problems. The server changed the path to the SQL tag library <%@ taglib uri="/jccrsrc/misc/jakarta-taglib/dbtags.jar" prefix="sql" %> vs <%@ taglib uri="http://jakarta.apache.org/taglibs/dbtags" prefix="sql" %>.

sebastian-spears
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Image Search

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  1. Image Search Implementation Results Ken Schmidt

  2. Some Implementation Problems • The server changed the path to the SQL tag library <%@ taglib uri="/jccrsrc/misc/jakarta-taglib/dbtags.jar" prefix="sql" %> vs <%@ taglib uri="http://jakarta.apache.org/taglibs/dbtags" prefix="sql" %>

  3. More Implementation Problems • File format to upload image is MultipartRequest Stream, format needed for PixelGrabber is Toolkit Image, no conversion available • Path problems implementing pixelGrabber //load the just stored file as an Image object Toolkit toolkit = Toolkit.getDefaultToolkit(); Image img = toolkit.getImage ( new java.net.URL ( "http://www.mycgiserver.com/~kenwschmidt/search/" + outfile ) ); //wait for entire image to be loaded before proceeding MediaTracker mediaTracker = new MediaTracker ( new Frame ( ) ); mediaTracker.addImage ( img, 0 ); mediaTracker.waitForID ( 0 ); // out.println ("<p>width of Image ="+img.getWidth(null) // + "</p><p>height of Image ="+img.getHeight(null) + "</p>"); //put the Image pixels in the pixels[] array PixelGrabber pg = new PixelGrabber(img, 0, 0, width, height, pixels, 0, width); try { pg.grabPixels(); }

  4. Calculating Pixel Values for DB • Run through pixel array twice, once to obtain the mean • Second time to calculate moments redSum2 +=Math.pow ( ( red - redMean), 2 ); greenSum2 += Math.pow ( ( green- greenMean), 2 ); blueSum2 +=Math.pow ( ( blue-blueMean ),2 ); redSum3 +=Math.pow ( ( red - redMean ), 3 ); greenSum3 +=Math.pow ( ( green- greenMean), 3 ); blueSum3 +=Math.pow ( ( blue- blueMean), 3 ); redSum4 +=Math.pow ( ( red - redMean), 4 ); greenSum4 +=Math.pow ( ( green- greenMean), 4 ); blueSum4 +=Math.pow ( ( blue- blueMean), 4 ); • Then enter all values into DB

  5. Now to Search the DB • Three steps • View all Items in the DB, Select one to match • Enter search criteria • Percent deviation from mean and moment values • Which DB values to search • Retrieve images whose mean or moment values are within the limits • Calculate the upper and lower limits of each value (1  ( deviation %/100 ) ) • Select images within the limits • select * from search where OVERALLMEAN BETWEEN <%=overallMeanDown%> AND <%=overallMeanUp%>

  6. CM-Color Mean GM-Grayscale Mean C2-Color Second Moment G2-Grayscale Second Moment Some ResultsWhich Search Methods Worked?

  7. More ResultsWhich Search Methods Worked?

  8. More ResultsWhich Search Methods Worked?

  9. More ResultsWhich Search Methods Worked?

  10. Conclusions • In each case, taking pixels grouped by color seemed to produce better results than taking all colors together • The third moment did not work well, because it can produce both positive and negative values and I only allowed a deviation maximum of 100% of the value of the search image • The Cambridge Lab used color and texture without image segmentation in combination, I used them separately so that I could see which method produced the best results.

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