Advanced shape context for plant species identification using leaf image retrieval

Mouine, Sofiène; Yahiaoui, Itheri; Verroust-Blondet, Anne

doi:10.1145/2324796.2324853

Cited by 58 publications

(43 citation statements)

References 28 publications

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“…using the Harris (corner) detector [38]. By simple visual inspection, some leafs with strong (well delimited) lobes and/or teeth (with clear associated convexity tips) may see their dominant veins well approximated by medial hot spots; but this is clearly not the case for many other leaf types with rather smooth outlines [27].…”

Section: Resultsmentioning

confidence: 99%

Point-based medialness for 2D shape description and identification

Aparajeya

Leymarie

2015

Multimed Tools Appl

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We propose a perception-based medial point description of a natural form (2D: static or in articulated movement) as a framework for a shape representation which can then be efficiently used in biological species identification and matching tasks. Medialness is defined by adapting and refining a definition first proposed in the cognitive science literature when studying the visual attention of human subjects presented with articulated biological 2D forms in movement, such as horses, dogs and humans (walking, running). In particular, special loci of high medialness for the interior of a form in movement, referred to as "hot spots", prove most attractive to the human perceptual system. We propose an algorithmic process to identify such hot spots. In this article we distinguish exterior from interior shape representation. We further augment hot spots with extremities of medialness ridges identifying significant concavities (from outside) and convexities (from inside). Our representation is strongly footed in results from cognitive psychology, but also inspired by know-how in art and animation, and the algorithmic part is influenced by techniques from more traditional computer vision. A robust shape matching algorithm is designed that finds the most relevant targets from a database of templates by comparing feature points in a scale, rotation and translation invariant way. The performance of our method has been tested on several databases. The robustness of the algorithm is further tested by perturbing the data-set at different levels.

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Section: Resultsmentioning

confidence: 99%

Point-based medialness for 2D shape description and identification

Aparajeya

Leymarie

2015

Multimed Tools Appl

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“…-A shape context based descriptor SC2 that represents the salient points of the leaf (essentially venation points) in the context defined by the leaf boundary [5].…”

Section: Plant Identification Methodsmentioning

confidence: 99%

An android application for leaf-based plant identification

Mouine

Yahiaoui

Verroust-Blondet

et al. 2013

Proceedings of the 3rd ACM Conference on International Conference on Multimedia Retrieval

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This paper presents an Android application for plant identification. The system relies on the observation of leaf images. Unlike other mobile plant identification applications, t h eu s e rm a yc h o o s et h el e a fc h a r a c t e r st h a tw i l lg u i d et h e identification process. For this purpose, two kinds of descriptors are proposed to the user: a shape descriptor based on a multiscale triangular representation of the leaf margin and a descriptor of the salient points of the leaf. The application achieves good identification accuracy and provides Android users a useful system for plant identification.

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“…We therefore see an increasing interest in this transdisciplinary challenge in the multimedia community (e.g. in [6,7,8,9,10,11]). Beyond the raw identification performances achievable by state-of-theart computer vision algorithms, recent visual search paradigms actually offer much more efficient and interactive ways of browsing large flora than standard field guides or online web catalogs [12].…”

Section: Introductionmentioning

confidence: 99%