Comparative Performance Evaluation of XYZ Plane Based Segmentation and Entropy Based Segmentation for Pest detection

Abstract

Image segmentation is the process of partitioning an image into multiple segments. The purpose of segmentation is to decompose the image into parts that are meaningful with respect to a particular application. In modern crop status management in greenhouse, instead of doing manually, crop status is monitored using cameras with some automation. One of the major problems in the greenhouse crop production is the presence of pests. An accurate and timely monitoring of pests population is the basic requirement. In the pest detection, image segmentation is one of the desirable steps to distinguish the pest from rest of part of an image. This work suggests two methods, namely ‘Segmentation using XYZ plane’ and ‘Entropy based histogram thresholding’. In the first method, XYZ color plane followed by thresholding is used instead of RGB space to overcome with some major problems in segmentation. The second method is given in which the maximum information content is used to decide the segmentation rule. Results are dependent upon a color space selection. The suggested segmentation algorithm is applied for images of pest infected leaves. Results are compared.

Authors and Affiliations

Trupti Shrikant Bodhe, Prachi Mukherji

Keywords

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  • EP ID EP120195
  • DOI -
  • Views 78
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How To Cite

Trupti Shrikant Bodhe, Prachi Mukherji (2013). Comparative Performance Evaluation of XYZ Plane Based Segmentation and Entropy Based Segmentation for Pest detection. International Journal of Computational Engineering and Management IJCEM, 16(2), 19-24. https://europub.co.uk/articles/-A-120195