License plate recognition with hierarchical temporal memory model; The 9th International Forum on on Strategic Techology (IFOST-2014), September 21-23, 2014, Cox's Bazar, Bangladesh

Xehetasun bibliografikoak
Parent link:The 9th International Forum on on Strategic Techology (IFOST-2014), September 21-23, 2014, Cox's Bazar, Bangladesh.— 2014.— [P. 136-139]
Egile nagusia: Bolotova Yu. A. Yuliya Aleksandrovna
Erakunde egilea: Томский политехнический университет Институт кибернетики, ИК
Beste egile batzuk: Druki A. A. Aleksey Alekseevich, Spitsyn V. G. Vladimir Grigorievich
Gaia:Title screen
Development of high quality license plate recognition system is a challenging task, not fully solved nowadays. License plate recognition process consists of the following steps: license plate detection, individual characters segmentation and recognition. This paper contains methods, connected with license plate allocation, segmentation and characters recognition. The noise on the plate and its angular inclination are main problems raised during developing such systems. In this article a new method of license plate recognition is presented. The proposed method includes preliminary image filtering, connected component method for segmentation and hierarchical temporal memory model for recognition. Image prefiltering improves the efficiency of subsequent binarization. Generally, license plate segmentation is provided by the histogram method, with different angles of inclination of the registration plate. As a result the rotation of the plate reduces the image quality. The connected component method eliminates rotation from this process, and provides no loss of image quality. Separate symbols can be represented under a small angle after such segmentation, which could complicate their identification. However, the application of the hierarchical temporal memory model for character recognition, previously trained at the sloping characters images, gives positive results. The proposed algorithms can also be used for distorted text segmentation and recognition.
Режим доступа: по договору с организацией-держателем ресурса
Hizkuntza:ingelesa
Argitaratua: 2014
Gaiak:
Sarrera elektronikoa:http://dx.doi.org/10.1109/IFOST.2014.6991089
Formatua: Baliabide elektronikoa Liburu kapitulua
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=641644

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200 1 |a License plate recognition with hierarchical temporal memory model  |f Yu. A. Bolotova, A. A. Druki, V. G. Spitsyn 
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320 |a [References: p. 139 (16 tit.)] 
330 |a Development of high quality license plate recognition system is a challenging task, not fully solved nowadays. License plate recognition process consists of the following steps: license plate detection, individual characters segmentation and recognition. This paper contains methods, connected with license plate allocation, segmentation and characters recognition. The noise on the plate and its angular inclination are main problems raised during developing such systems. In this article a new method of license plate recognition is presented. The proposed method includes preliminary image filtering, connected component method for segmentation and hierarchical temporal memory model for recognition. Image prefiltering improves the efficiency of subsequent binarization. Generally, license plate segmentation is provided by the histogram method, with different angles of inclination of the registration plate. As a result the rotation of the plate reduces the image quality. The connected component method eliminates rotation from this process, and provides no loss of image quality. Separate symbols can be represented under a small angle after such segmentation, which could complicate their identification. However, the application of the hierarchical temporal memory model for character recognition, previously trained at the sloping characters images, gives positive results. The proposed algorithms can also be used for distorted text segmentation and recognition. 
333 |a Режим доступа: по договору с организацией-держателем ресурса 
463 0 |0 (RuTPU)RU\TPU\network\4213  |t The 9th International Forum on on Strategic Techology (IFOST-2014), September 21-23, 2014, Cox's Bazar, Bangladesh  |o [proceedings]  |v [P. 136-139]  |d 2014 
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700 1 |a Bolotova  |b Yu. A.  |c Specialist in the field of informatics and computer technology  |c Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences  |f 1986-  |g Yuliya Aleksandrovna  |3 (RuTPU)RU\TPU\pers\33458  |9 17139 
701 1 |a Druki  |b A. A.  |c specialist in the field of informatics and computer technology  |c assistant of Tomsk Polytechnic University, engineer  |f 1985-  |g Aleksey Alekseevich  |3 (RuTPU)RU\TPU\pers\34610  |9 17972 
701 1 |a Spitsyn  |b V. G.  |c specialist in the field of informatics and computer technology  |c Professor of Tomsk Polytechnic University, Doctor of technical sciences  |f 1948-  |g Vladimir Grigorievich  |3 (RuTPU)RU\TPU\pers\33492  |9 17160 
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