<![CDATA[Indonesia is a tropical country that has no less than 4,000 types of trees. Potential tree species estimated 400 botanical species (species), included in 198 genera (genus) of the 68 tribes (families). Anatomical features include composition, shape, and size of cell or tissue intruders, which can only be observed clearly by using the aid of a magnifying glass like a magnifying glass or microscope. Along with the development of computerized technology, pattern recognition has much to do with a variety of applications and algorithms. One technique to identify an image is to distinguish the texture are the basic components forming the image. This study developed a computer-based technologies to perform pattern recognition (image). The system uses image recognition wood type pore structure of the wood. The introduction of wood types to apply the concept of content-based image retrieval (CBIR) using the algorithm Eigenimage. Identification is done by pattern matching. The test results by using 129 sample, showed the percentage of the system's ability to identify the image timber correctly by 97% (sensitivity), the percentage of the system's ability to recognize the type of wood does not match the sample, 58% (specificity), positive predictive value of 90% (PPV), a negative predictive value of 83% (NPV), and accuracy rate of 89% with an error rate of 11%.]]>
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