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Sandhiya, M.
- Scanned Image Segmentation and Detection Using MSER Algorithm
Authors
1 Angel College of Engineering and Technology, Tirupur., IN
Source
Digital Image Processing, Vol 9, No 6 (2017), Pagination: 115-118Abstract
Today’s modern medical imaging research faces the challenge of detecting brain tumour, skin cancer through scanned images. Normally, to produce images of soft tissue of human body, scanned images are used by experts. It is used for analysis of human organs to replace surgery. The brain tumour detection, or to find skin cancer image segmentation is required. For this purpose, the brain or skin is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumour and skin cancer. Hence, it is highly necessary that segmentation of the scanned images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of scanned images by using different tools and techniques. However, this paper presents a comprehensive review of the methods and techniques used to detect brain tumour and cancer and etc.., through scanned image segmentation. Lastly, the paper concludes with a concise discussion and provides a direction toward the upcoming trend of more advanced research studies on brain image segmentation and Tumour and Cancer detection.
Keywords
Scanned Image, Embedded Noise, Median Filter, MSER Algorithm.
References
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- Challenges and Future Changes in Big Data
Authors
1 Department of Computer Science, Dr.N.G.P. Arts and Science College, Coimbatore, IN
Source
Programmable Device Circuits and Systems, Vol 11, No 12 (2019), Pagination: 197-201Abstract
Big Data contains extremely large data sets. It contains both structured and unstructured data. It is very difficult to process such a massive amount of data by using the traditional methods. The use of Big Data is very common these days. The data is collected from different kinds of sources. So that a large volume of data is created. There are many benefits of Big Data. Now a days each and every company uses Big Data in many ways. Both small scale and large-scale companies use Big Data to gain information for providing better customer service. Big Data Analytics are now in demand because Big Data is now used in many business organizations. Even though there are many benefits, there are also certain challenges in handling and analyzing the Big Data. This paper provides a clear introduction of Big Data. It also contains the challenges faced in handling Big Data. This paper also discusses the future changes in Big Data.