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Hence, the precise identification of computer graphic and photographic image (PG) is a significant and challenging task. In the last two decades, several researchers have proposed different algorithms with impressive accuracy rate, including a recent addition of deep learning methods. This comprehensive survey presents techniques dealing with CG and PG image classification using machine learning and deep learning. In the beginning, broad classification of all the methods in to five categories is discussed in addition to generalized framework of CG detection. Subsequently, all the significant works are surveyed and are grouped into five types: image statistics methods, acquisition device properties-based techniques, color, texture, and geometry-based methods, hybrid methods, and deep learning methods. The advantages and limitations of CG detection methods are also presented. Finally, major challenges and future trends in the CG and PG image identification field are discussed.<\/jats:p>","DOI":"10.1142\/s0219467823500377","type":"journal-article","created":{"date-parts":[[2022,7,5]],"date-time":"2022-07-05T09:30:08Z","timestamp":1657013408000},"source":"Crossref","is-referenced-by-count":4,"title":["A Systematic Survey on Photorealistic Computer Graphic and Photographic Image Discrimination"],"prefix":"10.1142","volume":"23","author":[{"given":"Gajanan K.","family":"Birajdar","sequence":"first","affiliation":[{"name":"Department of Electronics Engineering, Ramrao Adik Institute of Technology, DY Patil deemed to be University Nerul, Navi Mumbai, Maharashtra 400706, India"}]},{"given":"Mukesh D.","family":"Patil","sequence":"additional","affiliation":[{"name":"Department of Electronics & Telecommunication Engineering, Ramrao Adik Institute of Technology, DY Patil deemed to be University Nerul, Navi Mumbai, Maharashtra 400706, India"}]}],"member":"219","published-online":{"date-parts":[[2022,7,5]]},"reference":[{"key":"S0219467823500377BIB001","first-page":"1","volume-title":"10th Int. 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