Friday 26th of April 2024
 

Plant Leaf Segmentation Using Non Linear K means Clustering


N.Valliammal and S. N. Geethalakshmi

This paper presents a new approach for plant leaf image segmentation by applying non linear k means algorithm. The segmentation process presents a clustering mechanism for high resolution images in order to improve the precision and processing time. Plant image, however, always contain complicated background objects that interfere with the examination process and must be removed from the image prior to species classification. K means clustering is applied at the first level of segmentation to detect the structure of the plant leaf. At the second level Sobel edge detector is used to remove the unwanted segments to extract the exact part of the leaf shape. The performance of the proposed method is compared with other traditional methods to analyze the efficiency of the system. Experimental result shows that this new approach simplifies the process to extract shape related features and measurements of the leaf for higher accuracy.

Keywords: Edge Detection, Sobel Edge Detector, K means clustering, Plant Leaf Identification.

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ABOUT THE AUTHORS

N.Valliammal
Working as Assistant Professor in Computer Science.

S. N. Geethalakshmi
Working as Associate Professor in Computer Science.


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