An approach to improve the classification accuracy of leaf images with dorsal and ventral sides by adding directionality features with statistical feature sets

Arun Kumar; Vinod Patidar; Deepak Khazanchi; G. Purohit; Poonam Saini

doi:10.1007/978-981-10-1023-1_9

An approach to improve the classification accuracy of leaf images with dorsal and ventral sides by adding directionality features with statistical feature sets

Arun Kumar, Vinod Patidar, Deepak Khazanchi, G. Purohit, Poonam Saini

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

The basic purpose of this work is to study statistical feature set obtained from digital leaf image with dorsal and ventral sides and to find the degree of classification accuracy for each dorsal and ventral leaf image dataset. Moreover, the effect of adding directional features to statistical feature set on the overall classification accuracy, is also investigated. The work also studies whether the ventral side of the digital leaf image can be a suitable alternative for classification of leaf image data set or not.

Original language	English (US)
Title of host publication	Advanced Computing and Communication Technologies - Proceedings of the 9th ICACCT, 2015
Editors	H.A. Nagarajaram, Ramesh K. Choudhary, Jyotsna Kumar Mandal, Nitin Auluck
Publisher	Springer Verlag
Pages	89-97
Number of pages	9
ISBN (Print)	9789811010217
DOIs	https://doi.org/10.1007/978-981-10-1023-1_9
State	Published - 2016
Event	9th International Conference on Advanced Computing and Communication Technologies, ICACCT 2015 - New Delhi, India Duration: Nov 28 2015 → Nov 29 2015

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	452
ISSN (Print)	2194-5357

Other

Other	9th International Conference on Advanced Computing and Communication Technologies, ICACCT 2015
Country/Territory	India
City	New Delhi
Period	11/28/15 → 11/29/15

Keywords

Directionality
Dorsal and ventral sides
Leaf images
Statistical features

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-981-10-1023-1_9

Cite this

Kumar, A., Patidar, V., Khazanchi, D., Purohit, G., & Saini, P. (2016). An approach to improve the classification accuracy of leaf images with dorsal and ventral sides by adding directionality features with statistical feature sets. In H. A. Nagarajaram, R. K. Choudhary, J. K. Mandal, & N. Auluck (Eds.), Advanced Computing and Communication Technologies - Proceedings of the 9th ICACCT, 2015 (pp. 89-97). (Advances in Intelligent Systems and Computing; Vol. 452). Springer Verlag. https://doi.org/10.1007/978-981-10-1023-1_9

An approach to improve the classification accuracy of leaf images with dorsal and ventral sides by adding directionality features with statistical feature sets. / Kumar, Arun; Patidar, Vinod; Khazanchi, Deepak et al.
Advanced Computing and Communication Technologies - Proceedings of the 9th ICACCT, 2015. ed. / H.A. Nagarajaram; Ramesh K. Choudhary; Jyotsna Kumar Mandal; Nitin Auluck. Springer Verlag, 2016. p. 89-97 (Advances in Intelligent Systems and Computing; Vol. 452).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kumar, A, Patidar, V, Khazanchi, D, Purohit, G & Saini, P 2016, An approach to improve the classification accuracy of leaf images with dorsal and ventral sides by adding directionality features with statistical feature sets. in HA Nagarajaram, RK Choudhary, JK Mandal & N Auluck (eds), Advanced Computing and Communication Technologies - Proceedings of the 9th ICACCT, 2015. Advances in Intelligent Systems and Computing, vol. 452, Springer Verlag, pp. 89-97, 9th International Conference on Advanced Computing and Communication Technologies, ICACCT 2015, New Delhi, India, 11/28/15. https://doi.org/10.1007/978-981-10-1023-1_9

Kumar A, Patidar V, Khazanchi D, Purohit G, Saini P. An approach to improve the classification accuracy of leaf images with dorsal and ventral sides by adding directionality features with statistical feature sets. In Nagarajaram HA, Choudhary RK, Mandal JK, Auluck N, editors, Advanced Computing and Communication Technologies - Proceedings of the 9th ICACCT, 2015. Springer Verlag. 2016. p. 89-97. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-981-10-1023-1_9

Kumar, Arun ; Patidar, Vinod ; Khazanchi, Deepak et al. / An approach to improve the classification accuracy of leaf images with dorsal and ventral sides by adding directionality features with statistical feature sets. Advanced Computing and Communication Technologies - Proceedings of the 9th ICACCT, 2015. editor / H.A. Nagarajaram ; Ramesh K. Choudhary ; Jyotsna Kumar Mandal ; Nitin Auluck. Springer Verlag, 2016. pp. 89-97 (Advances in Intelligent Systems and Computing).

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abstract = "The basic purpose of this work is to study statistical feature set obtained from digital leaf image with dorsal and ventral sides and to find the degree of classification accuracy for each dorsal and ventral leaf image dataset. Moreover, the effect of adding directional features to statistical feature set on the overall classification accuracy, is also investigated. The work also studies whether the ventral side of the digital leaf image can be a suitable alternative for classification of leaf image data set or not.",

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An approach to improve the classification accuracy of leaf images with dorsal and ventral sides by adding directionality features with statistical feature sets

Abstract

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Keywords

ASJC Scopus subject areas

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