Tree clustering for layout-based document image retrieval

Author(s):  
S. Marinai ◽  
E. Marino ◽  
G. Soda





2019 ◽  
Vol 121 ◽  
pp. 97-114 ◽  
Author(s):  
Fahimeh Alaei ◽  
Alireza Alaei ◽  
Umapada Pal ◽  
Michael Blumenstein


Author(s):  
Aliya Batur ◽  
Patigul Mamat ◽  
Wenjie Zhou ◽  
Yali Zhu ◽  
Kurban Ubul


Author(s):  
Ubul Kurban ◽  
Amat Ayxemgul ◽  
Aysa Yunus ◽  
Yadikar Nurbiya ◽  
Aizezi Yasen ◽  
...  


2018 ◽  
Vol 7 (3.1) ◽  
pp. 13
Author(s):  
Raveendra K ◽  
R Vinoth Kanna

Automatic logo based document image retrieval process is an essential and mostly used method in the feature extraction applications. In this paper the architecture of Convolutional Neural Network (CNN) was elaborately explained with pictorial representations in order to understand the complex Convolutional Neural Networks process in a simplified way. The main objective of this paper is to effectively utilize the CNN in the process of automatic logo based document image retrieval methods.  





Author(s):  
Eksan Firkat ◽  
Askar Hamdulla ◽  
Palidan Tuerxun ◽  
Abdusalam Dawut


Author(s):  
Yung-Kuan Chan ◽  
Tung-Shou Chen ◽  
Yu-An Ho

With the rapid progress of digital image technology, the management of duplicate document images is also emphasized widely. As a result, this paper suggests a duplicate Chinese document image retrieval (DCDIR) system, which uses the ratio of the number of black pixels to that of white pixels on the scanned line segments in a character image block as the feature of the character image block. Experimental results indicate that the system can indeed effectively and quickly retrieve the desired duplicate Chinese document image from a database.



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