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Plant Nutrient Deficiency<br />

Tee Seng Siong<br />

Supervisor: Dr. Abdul Aziz Bin K. Abd. Hamid<br />

Bachelor of Computer Science with Maritime Informatics<br />

School of Informatics and Applied Mathematics<br />

Classification of nutritional deficiencies, in a plant, is a problem for industry, since they<br />

do not have the knowledge to identify nutritional deficiencies neither receive technical<br />

assistance. The use of expertise can be time consuming because it need to take back the<br />

sample to laboratory for further analysis. Besides that human are prone to exhaust their<br />

energy thus can lead to more error in discovering the nutrient deficiency while examine<br />

the plant. There is no integration between the technology and individual expertise. In this<br />

paper, we proposed color base image analysis and segmentation to analyze and classify<br />

the image of plant according to deficiency classes by using image processing. This<br />

algorithm works by analyzing the characteristic of the plant leaf using color space. After<br />

the feature of interest leaf are extracted, the system will classify it according to their<br />

deficiency. Thus, people just need to take picture of the plant leaf using their mobile<br />

phone to get the relevant information.<br />

686 | UMT UNDERGRADUATE RESEARCH DAY 2018

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