Contour Based Retrieval for Plant Species

Abstract

-Recognizing a p lant in any huge vegetation is a tedious work for us. We recognize a plant on the basis of its size, leaves, flowers, fru its, etc. Leaf is a part of the p lant wh ich can be found on plants almost in all seasons and most of the time we have to recognize plants on the basis of its leaf. But when dealing with leaf o f plant, it is important to consider the finer details of the contour representing the shape of the leaf. We are t rying to build a system which has a database of leaves of different plants and given a leaf, we find out the plant to which it may belong. In this paper, we present the results of tangential angle approach used for retrieval. A database of around one thousand leaves of different plants has been created. Each leaf image is preprocessed to extract its boundary. Then tangential angle approach is applied wh ich captures the angular details of the boundary of shape. We have done the testing for around 1000 leaves and on the basis of that recall, precision and error rate have been calculated to measure the effectiveness of the proposed method.

Automatic Recognition of Plant Leaves Using Parallel Combination of Classifiers

“…This stage aims to transform the objects into a vector of numeric values (i.e., feature vector). There are many types of features that can be extracted from an image, such as shape [8], texture [9], and color [10] features.…”

Beyond use statistics: Recall, precision, and relevance in the assessment and management of academic libraries

“…The same general methods can be used to assess the performance of search filters (Fontelo and Liu, 2011;Shaikh et al, 2011) and to evaluate the effectiveness of various search strategies within a single database (Agoritsas et al, 2012;Gehanno et al, 2009). Recall and precision are also central to the assessment of nonbibliographic IR systems such as those used to search for gene and protein sequences (O'Grady, 2007), recognize plant species based on leaf shape (Asrani and Jain, 2013), detect near-duplicate video files (Paisitkriangkrai et al, 2011), identify blood cell images (Seng and Mirisaee, 2011), retrieve patent designs that meet specified criteria (Zeng and Yang, 2012), and automatically remove patients' identifying information from medical records (Neamatullah et al, 2008).…”

A Heuristic Strategy for Sub-Optimal ThickEdged Polygonal Approximation of 2-D Planar Shape

“…Most of them can be classified into two categories: (1) Polygonal approximation approaches and (2) Corner detection approach [5]. We shall confine our discussion to polygonal approximation approach.…”