Journal of Information Technology & Software Engineering
Open Access
ISSN: 2165- 7866
+44 1300 500008
ISSN: 2165- 7866
+44 1300 500008
Shitala Prasad
University of Caen Normandy, France
Posters & Accepted Abstracts: J Inform Tech Softw Eng
In today's ubiquitous world of mobile devices, even common to farmers, introduce mobile Information and Communication Technologies (ICT) seeking a keen role in daily life. In mobile vision (MV) research, first the captured object/scene is represented into some mathematical transformation describing the shape, texture and/or colour information for there classification. But to understand the nature�s biodiversity along with MV are now proposed and used. In earlier days, farmers were totally dependent on clouds for rain can now look to Cloud Computing (CC) for their solutions to have better cultivation. Therefore, here we propose various ways services which a farmer can utilize via MCC on their handsets using Agriculture-asa- Service (AaaS). One of such service is plant species identification by using leaf information. Here, a novel low-cost efficient and accurate rotation-scale-translation invariant Angle View Projection (AVP) shape profile transform is proposed. AVP shape profile curve (a set of four shapelets) is compacted in frequency domain using Discrete Cosine Transform (DCT). Five different types of plant leaf datasets: Flavia dataset, Swedish database, 100 plant species leaves dataset, ICL leaf dataset and diseased leaf dataset. AgroMobile module offloads heave computational tasks to AgroCloud for analysis. The AVP experiments carried out indicates that the proposed system outperforms the state-of-the-art. AVP also outperforms with incomplete leaves caused due to the pathological and/or physiological phenomenon. This AVP shape profile based mobile plant biometric system is developed for general applications in our society to better understand the nature and helps in botanical studies and researches. The AaaS framework allows farmer�s to put their cloud in their pockets.