International Journal of Innovative Research in Computer and Communication EngineeringM. Suganya, M. Menaka, "Various Segmentation Techniques in Image Processing: A Survey", International Journal of Innovative Research in Computer and Communication Engineering, Vol.2, Special Issue 1, March 2014....
Image Processing Using Feature-Based Segmentation Techniques for the Analysis of Medical Images doi:10.3390/engproc2023059100Engineering ProceedingsRanjith, Christodoss PrasannaNatarajan, KrishnamoorthyMadhuri, SindhuRamakrishna, Mahesh ThyloreBhat, Chandrasekhar RohithVenkatesan, Vinoth Kumar...
T. Kubik, and M. Sugisaka, "Image segmentation techniques and their use in artificial life robot implementation", Journal of Artificial Life and Robotics, Vol. 7, No. 1-2, March, 2003, pp. 12-15, 2003.Kubik, Tomasz and Sugisaka, Masanori (2002). Image segmentation techniques and their...
These techniques include grayscale conversion, flipping, rotation, horizontal and vertical flipping, as well as translational transformations. Consequently, the training set is expanded by incorporating these techniques. Figure 6 Preprocessed block. Full size image Following the expansion of the training ...
By parsing an image’s complex visual data into specifically shaped segments, image segmentation enables faster, more advanced image processing. Image segmentation techniques range from simple, intuitive heuristic analysis to the cutting edge implementation of deep learning. Conventional image segmentation ...
Image processing techniques This section describes related work for defect detection and image smoothing, in order to process the sensor data. Hanbay et al. (2016), Mahajan et al. (2009) and Kumar (2008) have presented plenty of algorithms for fabric defect segmentation in the period between ...
in microscopy images. One issue is that deep learning techniques require a large set of groundtruth data which is impractical to annotate manually for microscopy volumes. This paper describes a 3D nuclei segmentation method using 3D convolutional neural networks. A set of synthetic volumes and the ...
In the past, examining and identifying diseases in medical field was a lengthy process. Image segmentation techniques are used in medical images to study the internal structures of the human body, detect tumors, identify bone fractures, and estimate tumor size, etc. Segmentation for X-ray images...
It is a crucial tool in medical image processing and has various applications such as tumor detection, surgical planning, and image analysis. Different techniques can be used for segmentation, including region-based and edge-based methods. AI generated definition based on: Handbook of Medical ...
This paper reviews segmentation techniques such as theory-based, region-based, thresholding, edge-based, Neural Network-based, Model-based, and Partial differential equation based on the basis of their functioning, utility, advantages, disadvantages, and applications....