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39 results for “fuzzy k-cluster”
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Research ArticleOpen accessIn the abstractSoft Clustering Based Exposition to Multiple Dictionary Bag of WordsK. S. Sujatha, B. VinodObject classification is a highly important area of computer vision and has many applications including robotics, searching images, face recognition, aiding visually impaired people, censoring images and many more. A new common method of classification that uses features is the Bag of Words approach. In this method a codebook of visual words is created using various clustering methods. For increasing … …Journal of Computer Science, Vol. 8, Issue 12 · 20 Dec 2012 · 6,389 accessesView PDFCite
Research ArticleOpen accessIn the abstractNovel Fuzzy Technique for Cancer Detection in Noisy Breast Ultrasound ImagesN. Alamelumangai, J. DeviShreeProblem statement: Detecting tumor areas in breast Ultrasound (US) images is a challenging task. The occurrence of benign areas in breast may result in false identification of malignant areas which may have serious outcome. Approach: The CAD system could act as a major function in the early detection of breast cancer and could decrease the death rate among women with … …American Journal of Applied Sciences, Vol. 9, Issue 5 · 12 Mar 2012 · 6,959 accessesView PDFCite
Research ArticleOpen accessIn the abstractSegmentation of Medical Image using Clustering and Watershed AlgorithmsM.C. Jobin Christ, R.M.S. ParvathiProblem statement: Segmentation plays an important role in medical imaging. Segmentation of an image is the division or separation of the image into dissimilar regions of similar attribute. In this study we proposed a methodology that integrates clustering algorithm and marker controlled watershed segmentation algorithm for medical image segmentation. The use of the conservative watershed algorithm for medical image analysis … …American Journal of Applied Sciences, Vol. 8, Issue 12 · 22 Oct 2011 · 8,780 accessesView PDFCite
Research ArticleOpen accessIn the abstractDermoscopic Image Segmentation using Machine Learning AlgorithmL. Padma Suresh, K.L. Shunmuganathan, S.H. Krishna VeniProblem statement: Malignant melanoma is the most frequent type of skin cancer. Its incidence has been rapidly increasing over the last few decades. Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. Approach: This study explains the task of segmenting skin lesions in … …American Journal of Applied Sciences, Vol. 8, Issue 11 · 7 Oct 2011 · 7,342 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Computer Aided Diagnosis System for Lung Cancer Detection\Using Support Vector MachineM. Gomathi, P. ThangarajProblem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage … …American Journal of Applied Sciences, Vol. 7, Issue 12 · 31 Dec 2010 · 8,285 accessesView PDFCite
Research ArticleOpen accessIn the abstractIncreasing the Reliability of Fuzzy Inference System-Based Skin DetectorAlaa Y. Taqa, Hamid A. JalabProblem statement: Skin detection is a common primitive for many human-related image processing applications, such as video surveillance, naked image filters and face detection. Skin color is considered as a useful and discriminating spatial feature for many applications, but it is not robust enough to deal with complex image environments. Skin tones range from dark (some Africans) to light white … …American Journal of Applied Sciences, Vol. 7, Issue 8 · 31 Aug 2010 · 7,138 accessesView PDFCite
Research ArticleOpen accessIn the abstractDirect Model Reference Adaptive Controller Based-On Neural-Fuzzy Techniques for Nonlinear Dynamical SystemsHafizah Husain, Marzuki Khalid, Rubiyah YusofThis paper presents a direct neural-fuzzy-based Model Reference Adaptive Controller (MRAC) for nonlinear dynamical systems with unknown parameters. The two-phase learning is implemented to perform structure identification and parameter estimation for the controller. In the first phase, similarity index-based fuzzy c-means clustering technique extracts the fuzzy rules in the premise part for the neural-fuzzy controller. This technique enables the recruitment … …American Journal of Applied Sciences, Vol. 5, Issue 7 · 31 Jul 2008 · 6,939 accessesView PDFCite
Research ArticleOpen accessIn the abstractMemory Convergence and Optimization with Fuzzy PSO and ACSSubhash C. Pandey, Dr. P. MisraAssociative neural memories are models of biological phenomena that allow for the storage of pattern associations and the retrieval of the desired output pattern upon presentation of a possibly noisy or incomplete version of an input pattern. In this study, we introduce fuzzy swarm particle optimization technique for convergence of associative neural memories based on fuzzy set theory. A Fuzzy … …Journal of Computer Science, Vol. 4, Issue 2 · 28 Feb 2008 · 7,169 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordSwarm Optimization Techniques for Segmenting Gel Electrophoresis ImagesSara Ibrahim Ibrahim, Mohamed Abd Allah Makhlouf, Ghada.S. El-Tawel, M.E. WahedGel Electrophoresis (GE) are discussed as the main tool to dissociate DNA sequences. It helps in analyzing the genome such that each image resulting from it consists of lanes that include several bands. Image segmentation plays the foremost role in image processing. It helps in producing accurate results in medical diagnosis. Image segmentation works by dividing an image into regions … …Current Research in Bioinformatics, Vol. 5, Issue 1 · 18 Jun 2016 · 8,092 accessesView PDFCite