Title: Variants, meta-heuristic solution approaches and applications for image retrieval in business - comprehensive review and framework
Authors: S. Umamaheswaran; K. Ganesh; N. Suresh Kumar; P.V. Rajendra Sethupathi; S.P. Anbuudayasankar
Addresses: Department of Computer Science and Engineering, Vickram College of Engineering, Enathi, Sivagangai, Madurai – 630561, India ' Supply Chain Management – Center of Competence, McKinsey Knowledge Center (McKC), McKinsey & Company, Inc., Ascendas International Tech Park, Crest, Phase-2, 13th Floor, C.S.I.R Road, Taramani, Chennai 600113, TamilNadu, India ' Velammal College of Engineering and Technology, Velammal Nagar, Viraganoor, Madurai 625009, TamilNadu, India ' Vaigai College of Engineering, Therkutheru Melur Taluk, Madurai 625122, TamilNadu,India ' Department of Mechanical Engineering, Amrita Vishwa Vidyapeetham, Coimbatore 641112, TamilNadu, India
Abstract: The aim of this paper is to review the current state of the art in image retrieval using meta-heuristics. Besides, this paper provides a wide survey on the technical achievements in the research area of image retrieval for business applications especially using meta-heuristics. This survey includes top 33 papers covering the research aspects of image features representation, extraction and system design. Further, based on the demand from real world applications, open research issues are identified and future research directions are suggested.
Keywords: variants; metaheuristics; image retrieval; literature review; business applications; image features; feature representation; feature extraction; system design.
International Journal of Business Information Systems, 2015 Vol.18 No.2, pp.160 - 197
Published online: 28 Mar 2015 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article