Pulse Coupled Neural Network Edge-Based Algorithm for Image Text Locating  

作　　者：张昕 孙富春 

机构地区：[1]State Key Lab of Intelligent Technology and Systems,Tsinghua National Laboratory for Information Science and Technology,Department of Computer Science and Technology,Tsinghua University

出　　处：《Tsinghua Science and Technology》2011年第1期22-30,共9页清华大学学报（自然科学版（英文版）

基　　金：Supported by the National Natural Science Foundation of China(No. 60625304);the National Key Project For Basic Research of China(Nos. G2007CB 311003 and 2009CB724002)

摘　　要：This paper presents a method for locating text based on a simplified pulse coupled neural network （PCNN）. The PCNN generates a firings map in a similar way to the human visual system with non-linear image processing. The PCNN is used to segment the original image into different planes and edges detected using both the PCNN firings map and a phase congruency detector. The different edges are integrated using an automatically adjusted weighting coefficient. Both the simplified PCNN and the phase congruency energy model in the frequency domain imitate the human visual system. This paper shows how to use PCNN by changing the compute space from the spatial domain to the frequency domain for solving the text location problem. The algorithm is a simplified PCNN edge-based （PCNNE） algorithm. Three comparison tests are used to evaluate the algorithm. Tests on large data sets show PCNNE efficiently detects texts with various colors, font sizes, positions, and uneven illumination. This method outperforms several traditional methods both in text detection rate and text detection accuracy.This paper presents a method for locating text based on a simplified pulse coupled neural network （PCNN）. The PCNN generates a firings map in a similar way to the human visual system with non-linear image processing. The PCNN is used to segment the original image into different planes and edges detected using both the PCNN firings map and a phase congruency detector. The different edges are integrated using an automatically adjusted weighting coefficient. Both the simplified PCNN and the phase congruency energy model in the frequency domain imitate the human visual system. This paper shows how to use PCNN by changing the compute space from the spatial domain to the frequency domain for solving the text location problem. The algorithm is a simplified PCNN edge-based （PCNNE） algorithm. Three comparison tests are used to evaluate the algorithm. Tests on large data sets show PCNNE efficiently detects texts with various colors, font sizes, positions, and uneven illumination. This method outperforms several traditional methods both in text detection rate and text detection accuracy.

关 键 词：simplified pulse coupled neural network phase congruency text location 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] P228[自动化与计算机技术—计算机科学与技术]