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2D Object Recognition Techniques: State-of-the-Art Work

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Abstract

Object recognition is one of the research area in the field of computer vision and image processing because of its varied applications in surveillance and security systems, biometrics, intelligent vehicle system, content based image retrieval, etc. Many researchers have already done a lot of work in this area, but still there are many issues like scale, rotation, illumination, viewpoint, occlusion, background clutter among many more that draw the attention of the researchers. Object recognition is the task of recognizing the object and labeling the object in an image. The main goal of this survey is to present a comprehensive study in the field of 2D object recognition. An object is recognized by extracting the features of object like color of the object, texture of the object or shape or some other features. Then based on these features, objects are classified into various classes and each class is assigned a name. In this paper, various feature extraction techniques and classification algorithms are discussed which are required for object recognition. As the deep learning has made a tremendous improvement in object recognition process, so the paper also presents the recognition results achieved with various deep learning methods. The survey also includes the applications of object recognition system and various challenges faced while recognizing the object. Pros and cons of feature extraction and classification algorithms are also discussed which may help other researchers during their initial period of study. In this survey, the authors have also reported an analysis of various researches that describes the techniques used for object recognition with the accuracy achieved on particular image dataset. Finally, this paper ends with concluding notes and future directions. The aim of this study is to introduce the researchers about various techniques used for object recognition system.

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Authors and Affiliations

  1. Department of Computer Science, Punjabi University, Patiala, India

    Monika Bansal

  2. Department of Computational Sciences, Maharaja Ranjit Singh Punjab Technical University, Bathinda, Punjab, India

    Munish Kumar

  3. Department of Computer Science, Baba Farid College, Bathinda, Punjab, India

    Manish Kumar

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  1. Monika Bansal
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  2. Munish Kumar
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  3. Manish Kumar
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Correspondence to Munish Kumar.

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We have surveyed on various object recognition techniques. Papers surveyed are experimented on standard datasets like Caltech-101, COIL-100, Pascal VOC 2007, etc.

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Bansal, M., Kumar, M. & Kumar, M. 2D Object Recognition Techniques: State-of-the-Art Work. Arch Computat Methods Eng 28, 1147–1161 (2021). https://doi.org/10.1007/s11831-020-09409-1

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