1 Reply Latest reply on Jul 29, 2013 3:39 AM by arron lee


    amalp Newbie


      I just installed jboss-3.2.OCR2_tomcat.4.1.18. Server ran ok but but lot of errors.

      Here is the first error. please someone tell me why is this error.

      2003-04-10 17:30:50,860 DEBUG [org.jboss.management.j2ee.LocalJBossServerDomain] handleNotification: javax.management.Notification[source=jboss.system:service=ServiceController,type= org.jboss.system.ServiceMBean.create,sequenceNumber=20,timeStamp=1050021050860,message=null,userData=jboss.jca:service=RARDeployer]
      2003-04-10 17:30:50,860 DEBUG [org.jboss.system.ServiceController] Creating dependent components for: jboss.jca:service=RARDeployer dependents are: []
      2003-04-10 17:30:50,860 DEBUG [org.jboss.system.ServiceController] Creating service jboss.jca:service=DataSourceDeployer
      2003-04-10 17:30:50,870 INFO [org.jboss.deployment.XSLSubDeployer] Creating
      2003-04-10 17:30:52,222 ERROR [org.jboss.deployment.XSLSubDeployer] Initialization failedjavax.xml.transform.TransformerConfigurationException: javax.xml.transform.TransformerException: javax.xml.transform.TransformerException: Failed calling setMethod method
      at org.apache.xalan.processor.TransformerFactoryImpl.newTemplates(TransformerFactoryImpl.java:946)
      at org.jboss.deployment.XSLSubDeployer.createService(XSLSubDeployer.java:169)
      at org.jboss.system.ServiceMBeanSupport.create(ServiceMBeanSupport.java:158)
      at sun.reflect.GeneratedMethodAccessor4.invoke(Unknown Source)


        • 1. Re: Jboss-3.2.OCR2_tomcat.4.1.18
          arron lee Newbie

          I have never used the OCR you mentioned above, so I have never met the errors. But I want to share some information about OCR with you:

          Actually, there are two basic types of core OCR algorithm, which may produce a ranked list of candidate characters.

          Matrix matching involves comparing an image to a stored glyph on a pixel-by-pixel basis; it is also known as "pattern matching" or "pattern recognition". This relies on the input glyph being correctly isolated from the rest of the image, and on the stored glyph being in a similar font and at the same scale. This technique works best with typewritten text and does not work well when new fonts are encountered. This is the technique the early physical photocell-based OCR implemented, rather directly.

          Feature extraction decomposes glyphs into "features" like lines, closed loops, line direction, and line intersections. These are compared with an abstract vector-like representation of a character, which might reduce to one or more glyph prototypes. General techniques of feature detection in computer vision are applicable to this type of OCR, which is commonly seen in "intelligent" handwriting recognition and indeed most modern OCR software. Nearest neighbour classifiers such as the k-nearest neighbors algorithm are used to compare image features with stored glyph features and choose the nearest match.

          Software such as Cuneiform and Tesseract use a two-pass approach to character recognition. The second pass is known as "adaptive recognition" and uses the letter shapes recognized with high confidence on the first pass to better recognize the remaining letters on the second pass. This is advantageous for unusual fonts or low-quality scans where the font is distorted (e.g. blurred or faded).You can refer to some professional OCR SDKs for help. And you'd better try its free trial package first then choose one whose way of processing is simple and fast. I t can save a lot of time for you. I hope you success. Good luck.


          Best regards,