This review presents various image segmentation methods using complex networks. Image segmentation is one of the important steps in image analysis as it helps analyze and understand complex images. At first, it has been tried to classify complex networks based on how it being used in image segmentation. In computer vision and image processing applications, image segmentation is essential for analyzing complex images with irregular shapes, textures, or overlapping boundaries. Advanced algorithms make use of machine learning, clustering, edge detection, and region-growing techniques. Graph theory principles combined with community detection-based methods allow for more precise analysis and interpretation of complex images. Hybrid approaches combine multiple techniques for comprehensive, robust segmentation, improving results in computer vision and image processing tasks.

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PurposeAs tourism development is an unquestionable part of every national growth policy, this study aims to introduce an integrated method employing MICMAC analysis for understanding the key strategic variables of Iran's tourism development system.Design/methodology/approachThe structural analysis with MICMAC method was used to determine the classification of variables, aimed at structuring ideas to deal with complex decision-making and help planners and policymakers formulate future-based strategies.FindingsThe cross-impact matrix was used to identify the development variables having the greatest impact on the development of Southeast Asian tourism to Iran. The results showed that among 43 variables, 10 have great potential as key variables in the future of Iran's tourism development.Research limitations/implicationsMICMAC, as a structural analysis technique, is regarded as being the most appropriate to identify the key variables in the development of the Iranian tourism system. The limitation was that the other tourism markets, apart from ASEAN tourists, and the tourism demand-side were excluded from this study.Practical implicationsThe present study indicates that identifying key factors that influence the supply side of Iran's tourism system is worthwhile. Consequently, the findings show how these key factors can play a vital role in long-range economic sustainability and lead to the development of Iran's tourism market to enhance globally its competitiveness as a destination to attract international ASEAN tourists.Originality/valueThis study is one of the first papers to focus on the development of Iran's tourism market from a supply-side through structural analysis. Its findings are valuable as they can be used by the tourism authorities in the process of developing future tourism scenarios for Iran.

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