Publication

Abstract : Coconut Harvesting is one of the marketing crops in India. Some of the factors affecting coconut yielding are pest attacks such as red palm weevil, Stem bleeding through developed cracks. The aging of the coconut trees builds cracks, holes on the coconut trucks. Pest attacks, Cracks, and holes development affect the growth of the coconuts and results in reduced cultivation of coconuts. By identifying and controlling pest attacks, we can achieve better crop production. This paper aims to identify and spot the cracks and holes on coconut trunks using image processing techniques. In our proposed model, Cracks and holes identification uses different image preprocessing steps and four edge detection methods, and the crack is spotted using the contouring method on morphological Images. The algorithm proposed is tested on 50 real-time coconut trunk images collected from the Guntur, Prakasam districts of Andhra Pradesh, and Kollam district of Kerala in India. In this paper, we compare four edge detection models with multiple preprocessing steps required to is identify Cracks and Holes. Canny provides 96%, Prewitt with 89%, Sobel operator with 70%, Laplacian with 65% of accuracies