01917nam a2200265 a 4500 vtls000077108 KUKTEM 20251114204602.0 140328t2013 my a f m 000 0 eng d THE0001770(Local) 201905131230 yusri 201404020843 Fida 201403280844 Fida 201403280844 Fida UMP QA76.76.A65 L44 2013 rs Bc. Lee, Sai Foong Texture recognition by using artificial neural network / Lee Sai Foong Kuantan, Pahang : UMP, 2013 xi, 38 p. : ill. ; 30 cm. + 1 CD-ROM Project paper (Bachelor of Computer Science (Computer Graphic and Multimedia)) -- Universiti Malaysia Pahang - 2013 Bibliography : p. 33-34 This thesis describes the texture recognition by using the Artificial Neural Network (ANN). There are hard to understand on how to perform the texture recognition on any new set of image data. Therefore, to ease up the process on texture recognition, ANN has been chosen as the classifier to enhance the process of the texture recognition. There are thirteen types of Brodatz textures are considered as the dataset for this research and five sets for each type texture with different level of histogram equalized, noise for the training dataset. Backpropagation algorithm is one of the methods for the ANN. After the feature is obtained from the dataset, the feature will be trained and classifier by using theBack-propagation algorithm. All in all, this project will tell us how the Back-propagation classifier help in texture recognition and how to increases the success rate in texture recognition. Application software Development Neural networks Decision support systems 0 0 0 1 20000 20000 2019-09-04 0 QA76.76.A65 L44 2013 rs Bc. 0000078969 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 10000 10000 2019-09-04 0 CD 7663 | QA76.76.A65 L44 2013 rs Bc. 0000078970 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 4587 4593 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*6502*9992