Analysis and design of neural network based image retrieval system for identification of species

Jain, Sneha; Laxmi, Vijaya

doi:10.1109/iccpeic.2016.7557195

Cited by 2 publications

References 7 publications

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Visual animal biometrics: survey

Kumar

Singh

2017

IET biom.

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Visual animal biometrics is an emerging research discipline in computer vision, pattern recognition and cognitive science. It is a promising research field that encourages new development of quantified algorithms and methodologies for representing, detection of visible features, phenotypic appearances of species, individuals and recognition of morphological and animal biometric characteristics. Furthermore, it also assists the study of animal trajectory and behaviours analysis of species. Currently, real-world applications of visual animal biometric systems are gaining more proliferation due to a variety of applications and use, enhancement of quantity and quality of the collection of extensive ecological data and processing. However, to advance visual animal biometrics will require integration of methodologies among the scientific disciplines involved. Such valuable efforts will be worthwhile due to the enormous perspective of this approach rests with the formal abstraction of phenomics, to build well-developed interfaces between different organisational levels of life. This study provides a comprehensive survey of visual animal biometric systems and recognition approaches for various species and individual animal based on their morphological image pattern and biometric characteristics. This comprehensive review paper encourages the multidisciplinary researchers, scientists, biologists and different research communities to design the better platforms for the development of efficient algorithms and learning models to solve the massive data processing, classification and identification of different species related problems.

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Visual animal biometrics: survey

Kumar

Singh

2017

IET biom.

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Content-based fauna image retrieval system

Mustaffa

San

2017

2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)

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Many animal species exist in this world and there are always new species being discovered each year. Therefore, it is very important that these valuable species be documented properly to be referred to in future. Numerous information retrieval systems for managing and documenting animal species today only allow users to search animal images and descriptions online via text-based input. Therefore, people without knowledge on the animal species or without Internet access are not able to search using the systems. Motivated by these issues, the focus of this work is to construct a colour-shape content-based image representation for fauna. Two orders of the Colour Moment are used to represent the colour feature while the imeans approach is used to represent the shape feature. Based on the conducted quantitative and qualitative studies, the proposed fusion method together with the Content-based Image Retrieval (CBIR) system are found to be very effective in retrieving animal images similar to the given query, able to provide reliable and useful information on animal species, an easy system to interact with, and has easy to understand and user-friendly interfaces.

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Analysis and design of neural network based image retrieval system for identification of species

Cited by 2 publications

References 7 publications

Visual animal biometrics: survey

Visual animal biometrics: survey

Content-based fauna image retrieval system

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