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The major limitation that existed in the traditional VC techniques is pixel expansion, in which pixel expansion is replaced with a number of sub-pixels in individual share, which causes a considerable impact on the contrast and resolution of the image that further gradually decreases the quality of the image. VC is named for its essential characteristics, such as transmitting the images with two or more shares with an equal number of black pixels and color pixel distribution. The secret message can be decrypted using Human Visual System (HVS). In this paper, 50 research papers are reviewed based on various classification algorithms, which are effectively used for the VC technique. The classification algorithms are categorized into three types, namely, meta-heuristic, heuristic, and evolutionary, and the research issues and challenges confronted by the existing techniques are reported in this survey. Moreover, the analysis is done based on the existing research works by considering the classification algorithms, tools, and evaluation metrics. <\/jats:p>","DOI":"10.1142\/s0219467823500596","type":"journal-article","created":{"date-parts":[[2022,9,3]],"date-time":"2022-09-03T04:34:01Z","timestamp":1662179641000},"source":"Crossref","is-referenced-by-count":2,"title":["Analysis of Various Visual Cryptographic Techniques and their Issues Based on Optimization Algorithms"],"prefix":"10.1142","volume":"23","author":[{"given":"A. S.","family":"Sajitha","sequence":"first","affiliation":[{"name":"Electronics and Communication Engineering, Karunya Institute of Technology and Sciences, Karunya Nagar, Coimbatore 641114, Tamil Nadu, India"},{"name":"Nehru College of Engineering and Research Centre, Near Lakkidi Railway Station, Pampady, Thiruvilwamala 680588, Kerala, India"}]},{"given":"S. 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