Oriental Journal of Computer Science and Technology

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Cloud powered Plant Image Warehouse


Affiliations
1 ICAR, NAARM Rd, Acharya Ng Ranga Agricultural University, Rajendranagar mandal, Hyderabad, Telangana, India
 

Cloud powered plant image warehouse serves as an instrumental solution for various scientific and academic personnel involved in research, education and extension at NARES (National Agricultural Research and Education System), through providing a common image dataset that complements for efficient and more productive activities by saving them time, space, hassle and financial resources. This web based image repository enables the entire scientific community to access the freely available resources contributed by the fellow researchers who worked on common areas of interest, besides facilitating to acknowledge the one who originally contributed. This also enables them to have better control and use of meta data with tagging and custom theme usage. The Plant image warehouse has been developed by using XAMPP an open source platform, which works on the Cent OS, using Apache Web server and MySQL a relational web based data management system and PHP, the object oriented scripting language. The third party software used in developing this image warehousing database is ZenPHOTO, a configurable software system wherein the users are able to upload, search and share the images. The graphical user interface is restricted to static webpages where, upon request from the user, server sends the response unchanged, unless modified by the uploader. This potential plant image warehousing technique will outstand as an authentic and reliable source of plant image database to the entire working community at NARES (National Agricultural Research and Education System).

Keywords

Cloud Storage, Database, Plant Image Warehouse, ZenPHOTO.
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  • www.zenphoto.org: Technical manual about ZenPHOTO.

  • Barbedo, J. G. A. (2018). Factors Influencing the Use of Deep Learning for Plant Disease Recognition. Biosystems Engineering, 172, 84-91.

  • David P. Hughes and Marcel Salathe. (2015). An open access repository of images on plant health to enable the development of mobile disease diagnostics. https://arxiv.org/ftp/arxiv/papers/1511/1511.08060.pdf

  • Groff JR and PN Weinberg (2000). SQL Complete Reference. Tata McGraw Hill.

  • Guillaume Lobet, Xavier Draye, Claire Perilleux (2013). An online database for plant image analysis software tools. Open Access, http://www.plantmethods.com/content/9/1/38.

  • Ramez Elmasri and Navathe B. Shamkant (1994). Fundamentals of Database SystemsFunctional Dependencies and Normalization for Relational Databases, Addison-Wesley Publishing Company.

  • Thomas Mosgaard Giselsson, Rasmus Nyholm Jorgensen, Peter Kryger Jensen, Mads Dyrmann and Henrik Skov Midtiby (2017). A Public image database for Benchmark of Plant seedling classification Algorithms, Open access.

  • Waleed Al Shehri (2013). Cloud Database: Database as a service, International Journal of Database Management Systems (IJDMS) 5(2).


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  • Cloud powered Plant Image Warehouse

Abstract Views: 360  |  PDF Views: 1

Authors

V. V. Sumanth Kumar
ICAR, NAARM Rd, Acharya Ng Ranga Agricultural University, Rajendranagar mandal, Hyderabad, Telangana, India
Y. Praneetha
ICAR, NAARM Rd, Acharya Ng Ranga Agricultural University, Rajendranagar mandal, Hyderabad, Telangana, India
B. Padmaja
ICAR, NAARM Rd, Acharya Ng Ranga Agricultural University, Rajendranagar mandal, Hyderabad, Telangana, India
G. Lakshmana Murthy
ICAR, NAARM Rd, Acharya Ng Ranga Agricultural University, Rajendranagar mandal, Hyderabad, Telangana, India

Abstract


Cloud powered plant image warehouse serves as an instrumental solution for various scientific and academic personnel involved in research, education and extension at NARES (National Agricultural Research and Education System), through providing a common image dataset that complements for efficient and more productive activities by saving them time, space, hassle and financial resources. This web based image repository enables the entire scientific community to access the freely available resources contributed by the fellow researchers who worked on common areas of interest, besides facilitating to acknowledge the one who originally contributed. This also enables them to have better control and use of meta data with tagging and custom theme usage. The Plant image warehouse has been developed by using XAMPP an open source platform, which works on the Cent OS, using Apache Web server and MySQL a relational web based data management system and PHP, the object oriented scripting language. The third party software used in developing this image warehousing database is ZenPHOTO, a configurable software system wherein the users are able to upload, search and share the images. The graphical user interface is restricted to static webpages where, upon request from the user, server sends the response unchanged, unless modified by the uploader. This potential plant image warehousing technique will outstand as an authentic and reliable source of plant image database to the entire working community at NARES (National Agricultural Research and Education System).

Keywords


Cloud Storage, Database, Plant Image Warehouse, ZenPHOTO.

References