An Exhaustive Survey on Meta-Heuristic Algorithms for Unimodal and Multimodal Optimization
K. Kalaivani1, N. UmaMaheswari2
1K. Kalaivani, Department of Computer Science & Engineering, PSNA College of Engineering & Technology, Dindigul (Tamil Nadu), India.
2Dr. N. UmaMaheswari, Department of Computer Science & Engineering, PSNA College of Engineering & Technology, Dindigul (Tamil Nadu), India.
Manuscript received on 11 January 2020 | Revised Manuscript received on 07 February 2020 | Manuscript Published on 20 February 2020 | PP: 366-372 | Volume-9 Issue-3S January 2020 | Retrieval Number: C10790193S20/2020©BEIESP | DOI: 10.35940/ijitee.C1079.0193S20
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A review of the global feature color comprising of seven different metrics are discussed here. The color is the most powerful feature for describing the images. This study contains four sections. The first section explains the related techniques used in various papers. The second section explains the two different kinds of metrics. (1) Similarity metrics such as Cosine and Correlation and (2) Dissimilarity metrics such as Euclidean, Manhattan, Bhattacharyya, Chi-Squared and Intersection. The third section explains experiment results using CALTECHUCSD Birds-200 image library. The fourth section gives the conclusion and future work. In this experiment, the query image can be divided into trained (indexed) or untrained (non-indexed). In the similarity metric analysis, the experimental results show that the cosine similarity gives better similarity score than correlation. Similarly, in the dissimilarity metric analysis, the Bhattacharyya gives a better result than other distance metrics.
Keywords: Color Histogram, Similarity metric, Dissimilarity Metric, Cosine Similarity, Correlation Euclidean, Manhattan, Bhattacharyya, Chi-Squared and Intersection.
Scope of the Article: Web Algorithms