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Swati Singh,Sheifali Gupta 보안공학연구지원센터 2016 International Journal of Bio-Science and Bio-Techn Vol.8 No.4
The proposed paper surveys different techniques for early spotting and classification of diseased plant using digital image processing. As in agribusiness, agriculturists detect plant diseases straight through the bare eyes. This type of detection requires continuum supervisory which can be expensive as well as time consuming on large farms. Therefore, recognizing the disease on plants is of extreme importance in agriculture sector. The selected proposal is divided into three classes: detection, classification and extraction. The three classes are further sub divided according to the different algorithm. This paper provides an overview of different image processing techniques and classification methods.
Retinal Blood Vessel Segmentation Algorithms : A Comparative Survey
Meenu Garg,Sheifali Gupta 보안공학연구지원센터 2016 International Journal of Bio-Science and Bio-Techn Vol.8 No.3
Automated segmentation and delineation of morphological properties of retinal vascular network had now become the most important research area in the treatment of ophthalmologic disorders. With the advancement of computational efficiency, image processing methodologies are widely used in ophthalmology. This paper gives the review of various segmentation techniques implemented by various authors in conjunction with performance metrics like sensitivity, specificity, accuracy and area under the curve. Results of various algorithms has been compared and analyzed. For the extraction of retinal vasculature, 2D retinal image from various databases has been considered.
Memory Cell Designs with QCA Implementations: A Review
Amanpreet Sandhu,Sheifali Gupta 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.10
Quantum-dot-cellular-automata is a potential technology for low power and high density memory designs. In this paper a comprehensive review of parallel and serial QCA memory-cell designs are presented. It is shown that a loop-based serial memory-cell design is better in terms of latency, clocking and timing, hardware requirement.
Offline Handwritten Gurmukhi Character Recognition : A Review
Neeraj Kumar,Sheifali Gupta 보안공학연구지원센터 2016 International Journal of Software Engineering and Vol.10 No.5
All over India more than 12 crore people utilize Gurumukhi script for speaking, documenting & other purposes. A considerable advancement in the work associated with the recognition of handwritten and printed Gurmukhi text has been reported in last few years. From the last few decades offline handwritten character recognition has gained a lot of interest of researchers. It is well known that each individual has some different writing style, so it is very difficult to identify or recognize the handwritten characters. Researchers have worked in this field using various scripts like Hindi, English but a very little work has been done in Gurmukhi script point of view. Based on data acquirement process a concise classification of recognition system has been discussed in this article. Various feature mining techniques & classifiers like power arc fitting ,parabola arc fitting, ,diagonal feature extraction, transition feature extraction, K-NN classifier (K-nearest neighbor) & SVM classifier (Support vector machine) are also illustrated in this paper. The methodology for word recognition has also been discussed in this paper.