International Journal of Advance Computational Engineering and Networking (IJACEN)
.
Follow Us On :
current issues
Volume-10,Issue-3  ( Mar, 2022 )
Past issues
  1. Volume-10,Issue-2  ( Feb, 2022 )
  2. Volume-10,Issue-1  ( Jan, 2022 )
  3. Volume-9,Issue-12  ( Dec, 2021 )
  4. Volume-9,Issue-11  ( Nov, 2021 )
  5. Volume-9,Issue-10  ( Oct, 2021 )
  6. Volume-9,Issue-9  ( Sep, 2021 )
  7. Volume-9,Issue-8  ( Aug, 2021 )
  8. Volume-9,Issue-7  ( Jul, 2021 )
  9. Volume-9,Issue-6  ( Jun, 2021 )
  10. Volume-9,Issue-5  ( May, 2021 )

Statistics report
May. 2022
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 111
Paper Published : 1360
No. of Authors : 3436
  Journal Paper


Paper Title :
Paddy Leaves Nutrient Deficiency Detection using Image Processing Technique

Author :S. Sivagami, S. Mohanapriya

Article Citation :S. Sivagami ,S. Mohanapriya , (2020 ) " Paddy Leaves Nutrient Deficiency Detection using Image Processing Technique " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 29-33, Volume-8,Issue-11

Abstract : Image processing widely used in agriculture sector for finding problems like disease identification, weed detection, fruit grading etc., In this paper, work is carried out based on automatic deficiency detection of paddy leaves. Research of automatic leaf deficiency detection is essential research topic as it may prove benefits in monitoring large fields of crops, and thus automatically detect symptoms of deficiency as soon as they appear on plant leaves. Among all the grains rice is one of the most consumed grain in south India, but is easily affected by the nutrition deficiency. To increase the yield early identification of nutrient deficiencies of paddy crop is very essential. Paddy leaves color plays an important role in identifying micro deficiencies such as CSM (Calcium, Sulfur and Magnesium) during middle stage of its growth. Database of healthy, calcium defected, sulfur defected and magnesium defected leaves is created to identify deficient paddy leaves. HSV color model is used to extract Color features of both healthy and defected paddy leaves. Color features of test image is also extracted and compared against database properties. Comparison results are checkedwith the rules set to decide the specific deficiency. The rules are framed based on thorough experiment. Keywords - HSV, Image Processing, Calcium, Sulfur and Magnesium Deficiency

Type : Research paper

Published : Volume-8,Issue-11


DOIONLINE NO - IJACEN-IRAJ-DOIONLINE-17621   View Here

Copyright: © Institute of Research and Journals

| PDF |
Viewed - 52
| Published on 2021-02-22
   
   
IRAJ Other Journals
IJACEN updates
Paper Submission is open now for upcoming Issue.
The Conference World

JOURNAL SUPPORTED BY