01965nam a2200253 a 4500 vtls000076552 KUKTEM 20251114204557.0 140107t2012 my a f m 000 0 eng d THE0002951(Local) 201905140836 zul 201401070907 nabilah UMP TA1637 .R33 2012 rs Bc. Radhiah Zainon Paddy disease detection system using image processing / Radhiah Zainon Kuantan, Pahang : UMP, 2012 xii, 106 p. : ill. ; 30 cm. + 1 CD-ROM Project paper (Bachelor of Computer Science (Software Engineering)) -- Universiti Malaysia Pahang – 2012 Bibliography : p. 56-58 The main objectives of this research is to develop a prototype system for detect the paddy disease which are Paddy Blast Disease, Brown Spot Disease, Narrow Brown Spot Disease. This paper concentrate on the image processing techniques used to enhance the quality of the image and neural network technique to classify the paddy disease. The methodology involves image acquisition, pre-processing and segmentation, analysis and classification of the paddy disease. All the paddy sample will be passing through the RGB calculation before it proceed to the binary conversion. If the sample is in the range of normal paddy RGB, then it is automatically classify as type 4 which is Normal. Then, all the segmented paddy disease sample will be convert into the binary data in excel file before proceed through the neural network for training and testing. Consequently, by employing the neural network technique, the paddy diseases are recognized about 92.5 percent accuracy rates. This prototype has a very great potential to be further improved in the future. Image processing Rice Diseases and pests 0 0 0 1 10000 10000 2019-09-04 0 TA1637 .R33 2012 rs Bc. 0000079017 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 10000 10000 2019-09-04 0 CD 7686 | TA1637 .R33 2012 rs Bc. 0000079018 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 4423 4429 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*9992