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A platform for research: civil engineering, architecture and urbanism
Clustering of Odia Character Images Using K-Means Algorithm and Spectral Clustering Algorithm
Abstract Clustering refers to assembling of certain amount of data objects which are in some relation with each other into a single group. Massive information can be partitioned into number of suitable express piles using clustering techniques. Clustering can upsurge the competence of classification in case of large number of class labels. Since Odia language contains more than four hundred numbers of symbols, classification of those symbols are quite complex. To decrease the complexity of the classifier, clustering plays a crucial role by creating small groups of similar types of symbols. This paper contains the comparison result of clustering of vowel characters of Odia language by using the method k- means algorithm and spectral clustering basing on our proposed feature extraction technique. Among various techniques used for clustering the k-mean is being proved as simple, so commonly used for number of applications. Whereas spectral clustering is an emerging as well as popular modern clustering algorithm which clusters the data based on spectral decomposition.
Clustering of Odia Character Images Using K-Means Algorithm and Spectral Clustering Algorithm
Abstract Clustering refers to assembling of certain amount of data objects which are in some relation with each other into a single group. Massive information can be partitioned into number of suitable express piles using clustering techniques. Clustering can upsurge the competence of classification in case of large number of class labels. Since Odia language contains more than four hundred numbers of symbols, classification of those symbols are quite complex. To decrease the complexity of the classifier, clustering plays a crucial role by creating small groups of similar types of symbols. This paper contains the comparison result of clustering of vowel characters of Odia language by using the method k- means algorithm and spectral clustering basing on our proposed feature extraction technique. Among various techniques used for clustering the k-mean is being proved as simple, so commonly used for number of applications. Whereas spectral clustering is an emerging as well as popular modern clustering algorithm which clusters the data based on spectral decomposition.
Clustering of Odia Character Images Using K-Means Algorithm and Spectral Clustering Algorithm
Panda, Suneha (author) / Nayak, Mamata (author) / Nayak, Ajit Kumar (author)
2019-06-28
10 pages
Article/Chapter (Book)
Electronic Resource
English
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