PROCESSING OF IMAGES TO PREDICT AGE AND WEATHER IMPACT ON WOOD

Computer Science and Engineering

NATIONAL CONFERENCE ON TECHNOLOGICAL ADVANCEMENTS IN ENGINEERING

Processing of cross sectional view of a wood that predicts the age and its weather impact by using convolution theorem and SVM classifier. The cross sectional view of a wood (X-Ray image) is extracted from the tree and it is given as an input. Image is processed and converted into gray scale image in order to remove the noise which present in the cross sectional view of an image. The extracted image is converted into vector. Vector contains many tree ring structure, distance between two tree ring structures is predicted using distance calculation. Input image is matched with the trained image. Image stored in the database is classified using SVM classifier based on the distance between two tree ring structures. If the input image matches with trained image, it will retrieve age, weather impact and outer layer thickness of the wood The distance between two tree ring structure is used to classify and analyze age, weather impact and outer layer thickness of the wood by using SVM classifier. In the existing system two layered laminated wood is taken and processed. The laminated wood is pre-processed and it leads to wastage so the quality of wood cannot be predicted accurately. Two layered laminated wood contains more processing which is time consuming.

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