Gender Identification of Imperfect Flowers Using Image Classification

In this paper, we present two approaches that can be used to classify images of imperfect flowers according to their gender. By taking photos of small sections of the flower and that of objects in its neighborhood, it is possible to classify the imperfect flowers. Using images of bitter gourd flowers and various other objects, we tested our approaches. In the first approach, we used multilayer perceptron network in WEKA 3.8.0 on red, green and blue (RGB) components of the images and could classify all stamens and pistils correctly. In the second approach, we constructed a set of rules to classify images with hundred percent accuracy based on their RGB values. This has much less computational burden than the first approach.

• Publication year

  2018

• Venue

  International Conference on Autonomic and Trusted Computing

• Publication date

  2018-10-01

• Fields of study

  Biology, Computer Science

• Identifiers
  DOI 10.1109/ATC.2018.8587564
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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