Ancient Chinese Character Image Segmentation Based on Interval-Valued Hesitant Fuzzy Set

Abstract

To address the low segmentation accuracy caused by the rich glyph styles of ancient Chinese characters and the complex layout of ancient Chinese books, which affects the retrieval and recognition results, an algorithm for the layout image analysis of ancient Chinese books and Chinese character image segmentation is proposed. The initial segmentation results were obtained through the projection method of the layout of ancient Chinese books, and the connected component analysis of the above results was carried out to determine the rough divided blocks of under-segmentation and oversegmentation. Considering under-segmentation of adhesive Chinese characters, the improved K-means clustering method was used to segment adhesive blocks to obtain single-character images. To address the over-segmentation of character components separation, a method based on interval-valued hesitant fuzzy set is proposed. This method analyzed the features of the connected component in the block, characterized the over-segmentation connected component. The hesitant fuzzy distances between other connected components and the standard merge evaluation interval number were calculated in sequence. The connected component with the smallest distance was preferentially merged with the over-segmentation connected component until no over-segmentation connected component remained in the block. The experimental segmentation accuracy was 89.94%.

Research on the Prediction of world nuclear weapons Quantity based on Topsis Comprehensive Evaluation method

“…Since the world's first nuclear bomb came into view in 1945, nuclear weapons entered a period of rapid development, reaching its peak during the US-Soviet Cold War, when people became generally aware of the immense destructive power of nuclear weapons and began to limit the number of nuclear bombs to prevent their proliferation [4]. In the pursuit of a nuclear-free 21st century, it is necessary to collect descriptive statistics on the nuclear weapons of all countries in the world and, based on these data, to predict the total number of nuclear weapons in the world and in each country in the future, and before the number of nuclear weapons is zeroed out, to further develop mathematical models of the locations of nuclear weapons explosions and to further determine the threat of nuclear weapons to the planet on which humanity depends [5][6][7][8]. Based on the background information identified in the abstract and the data already collected on the web, the following questions were finally addressed [9].…”

Character Detection and Segmentation of Historical Uchen Tibetan Documents in Complex Situations

“…Qi et al [20] first used connected component analysis to obtain the initial character segmentation, then solved the attribution of Chinese characters in historical documents by establishing the hesitation fuzzy set, and finally analyzed the pixel jump to achieve the segmentation of touching and overlapping Chinese characters. Tian et al [21] improved the method of Qi et al, taking into account the problem of character undersegmentation and using the improved K-means to solve the problem of touching character segmentation. Zaw and War [22] proposed a method based on character connected component analysis to complete the segmentation of Myanmar touching characters.…”