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Panwar, Lal Chand
- Comparative Analysis of CAPTCHA Based Techniques: A Review
Abstract Views :155 |
PDF Views:2
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1 Department of Computer Engineering, Punjabi University, Patiala, IN
1 Department of Computer Engineering, Punjabi University, Patiala, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 12 (2014), Pagination: 79-85Abstract
CAPTCHA(Completely Automatic Public Turing test to tell Computers and Humans Apart ) is used by every website on the internet to prevent unauthorized user or bots to use the bandwidth and resources of the network. At the present time every user has to register on the website to access any type of information or resources so he/she has to pass the CAPTCHA test. If the user has passed the CAPTCHA test he/she is assumed to be legitimate user and can access resources or information from that site otherwise he/she is attacker or bots. So due to more attack on the web sites CAPTCHA is used to prevent these attacks. This is more popular technique used in present scenario. This paper focus on the scope of CAPTCHA,various types of CAPTCHA and its techniques.Keywords
CAPTCHA, Time Variant, Text Based, Gimpy, Bongo, MSN, iCAPTCHA, Color Based CAPTCHA.Full Text
- Identification and Detection of Plant Diseases Using Image Segmentation Techniques:A Review
Abstract Views :166 |
PDF Views:3
Authors
Affiliations
1 Department of Computer Engineering, Punjabi University, Patiala, IN
1 Department of Computer Engineering, Punjabi University, Patiala, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 24, No 1 (2017), Pagination: 12-18Abstract
This review paper discusses various image segmentation methods for parting plant images to identify infected part of leaf. Segmentation is an image processing system that is used to divide image into parts in light of pixel and auxiliary data. Segmentation is utilized to separate area of interest based on the application. This paper explains about area based and edge based segmentation methods under which thresholding, K-mean, Fuzzy C mean systems are examined.Full Text
References
- N. M. Zaitoun and M. J. A. , "Survey on Image Segmentation Techniques," 2015.
- U. M. S, M. C and S. M, "An Experiment Study and Analysis of Different Segmentation Techniques," 2013.
- Dilpreet and Y. K. , "Various Image Segmentation Techniques:A review," vol. 3, no. 5, 2014.
- G. Manoj and A. Rajamurugan, "A Review about Digital Image Segmentation Techniques," vol. 3, no. 9, 2015.
- R.Yogamangalam and B.Karthikeyan, "Segmentation Techniques Comparison in Image Processing," vol. 5, no. 1, 2013.
- S. Nilima, PatelDhanesh and JivaniAnjali, "Review on Image Segmentation, Clustering and Boundary Encoding," vol. 2, no. 11, 2013.
- P.Revathi and M.Hemalatha, "Classification of Cotton Leaf Spot Diseases Using Image Processing Edge Detection Technique," 2012.
- S. M. Sheela Se, "Study and Theortical Analysis of Various Segmentation Technique For Ultrasound Images," 2016.
- H. Narkhede, " Review Of Image Segmentation Techniques," no. 8, july 2013.
- A. Khan and R. S, "Image Segmentation Methods:A Comparitive Study," vol. 3, no. 4, 2013.
- Y. Chan and O.T.Chan, "Image Segmentation Method using Thtreshold Automatically Determined from Picture Content".
- A.Comargo and J. Smith, "Image Pattern Classification for the Identification of Disease Causing Agents In Plants," no. 66, 2009.
- A. B. Ishak, "A two Dimensional Multilevel Thresholding Method For Image Segmentation," no. 52.
- S. Sankaran, A. Mishra, R. Ehsani and C. Davis, no. 72, 2016.
- T. Liang, M. Zhang and W. N.Brown, "Image Feature Selection Using Genric Programming for Figure Ground Segmentation," no. 62, 2017.
- D. A. Bashish, M. Braik and S. Bani-Ahmed, "Detection and Classification of Leaf Diseases using K-means Based Segmentation and Nural Network Based Classification".
- A. N.Rathod, B. Tanawal and V. shah, "Image Processing Technique for Detection of leaf Disease," vol. 3, no. 11, 2013.