IJRCIT- International Journal of Research in Computer & Information Technology

Archives of International Journal of Research in Computer & Information Technology(IJRCIT)

Volume 7 Issue 4 September 2022

1. Proposed Methodology for Recognition of Plant Diseases by Leaf Image Classification Using Machine Learning

AUTHOR NAME : Prasad W. Bhombe, Dr. Shirish V. Pattalwar

ABSTRACT : Crop diseases are a noteworthy risk to sustenance security, however their quick distinguishing proof stays troublesome in numerous parts of the world because of the non-attendance of the important foundation. Emergence of accurate techniques in the field of leaf-based image classification has shown impressive results. This paper makes use of Random Forest in identifying between healthy and diseased leaf from the data sets created. Our proposed paper includes various phases of implementation namely dataset creation, feature extraction, training the classifier and classification. The created datasets of diseased and healthy leaves are collectively trained under Random Forest to classify the diseased and healthy images. For extracting features of an image, use Histogram of an Oriented Gradient (HOG). Overall, using machine learning to train the large data sets available publicly gives us a clear way to detect the disease present in plants in a colossal scale.

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2. Study of Steganographic Techniques for Data Hiding

AUTHOR NAME : Pankaj M. Bhuyar, Dr. S. W. Mohod

ABSTRACT : Nowadays, the volume of data shared over the Internet is growing. As a result, data security is referred to as a major issue while processing data communications through the Internet. During communication procedures, everyone requires their data to remain secure. Steganography is the science and art of embedding audio, message, video, or image into another audio, image, video, or message to conceal it. It is used to secure confidential information from harmful attacks. This research offers a classification of digital steganography based on cover object categories, as well as a classification of steganalysis art. Image visual quality, structural similarity, mean square error, Image Fidelity, embedding capacity, and robustness are some of the important aspects of steganography. Researchers have made tremendous advances in the realm of digital steganography. Nonetheless, it is vital to emphasize the advantages and disadvantages of modern steganography techniques. This paper first presents a literature survey of information hiding, then classifies the proposed methods, and finally introduces a comparative study between the different methods.

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