公开(公告)号：WO2019066642A3

公开(公告)日：2019-04-04

申请号：PCT/MY2018/050064

申请日：2018-09-28

Applicant: MIMOS BERHAD

Inventor： MOKAYED, Hamam ,  HON, Hock Woon ,  HUM, Yan Chai ,  SIANG, Kelvin Lo Yir ,  CHOO, Che Yon

IPC: G06K9/32 ,  G06K9/34

Abstract: The present invention relates to a system and method for detecting license plate. The system (100) comprises a plate detection module (20) configured to detect location of vehicle license plate by filtering noise using multi-masking technique, dynamic dilation and group-based filtering, wherein multi-masking technique generates a plurality of mask images to remove noise; wherein the dynamic dilation enhances white pixels based on strongly connected primary vertical, primary diagonal and secondary diagonal white pixels; and wherein the group-based filtering filters similar blobs based on compactness, ratio and white pixel density rules.

公开(公告)号：WO2017116226A1

公开(公告)日：2017-07-06

申请号：PCT/MY2016/050069

申请日：2016-10-21

Applicant: MIMOS BERHAD

Inventor： HUM, Yan Chai ,  LIANG, Kim Meng ,  HON, Hock Woon ,  MOKAYED, Hamam

IPC: G06K9/32 ,  G06K9/46

CPC classification number: G06K9/325 ,  G06K9/38

Abstract: The present disclosure relates to the field of automated identification plate recognition, and more particularly relates to automated identification plate recognition based on background estimation binarization. In an aspect, the present disclosure relates to a system for detecting and recognizing a vehicle identification plate, wherein system includes a plate detection module configured to detect location of the plate; a plate segmentation module that configured to segment characters in the detected plate into respective individual entities; a plate recognition module configured to recognize the individual entities of the detected plate as alphabets or numerals; and a plate post-analyzer module configured to determine full text of the detected plate, wherein the characters are segmented by the plate segmentation module by applying background estimation binarization in order to obtain the respective individual entities.

Abstract translation: 本公开涉及自动识别牌识别领域，并且更具体地涉及基于背景估计二值化的自动识别牌识别。 在一个方面，本公开涉及一种用于检测和识别车辆标识牌的系统，其中系统包括：板检测模块，其被配置为检测板的位置; 板块分割模块，其被配置为将检测到的板中的字符分割成各个单独的实体; 板识别模块，其被配置为将所检测板的各个实体识别为字母或数字; 以及板后分析器模块，其被配置为确定检测到的板的全文，其中通过应用背景估计二值化由板分割模块分割字符以便获得各个单独的实体。

公开(公告)号：WO2017091060A1

公开(公告)日：2017-06-01

申请号：PCT/MY2016/050068

申请日：2016-10-14

Applicant: MIMOS BERHAD

Inventor： MOKAYED, Hamam ,  LIANG, Kim Meng ,  HON, Hock Woon ,  HUM, Yan Chai ,  LO, Kelvin Yir Siang

IPC: G06K9/32 ,  G06K9/34 ,  G06K9/46 ,  G06K9/62

CPC classification number: G06K9/3258 ,  G06K9/342

Abstract: This disclosure describes a system and method for detecting objects from at least an image. Such invention is useful in detecting vehicle license plate and identifying the characters on the license plate. The method comprises steps of conducting edge-based technique (210) on the image for identifying Binary Large Objects (BLOBs) that potentially represent the objects upon binarizing the image; performing dynamic dilation (220) that determines different bodies of which the objects are respectively located thereon for identifying BLOBs of different objects that appear in a single image; applying group-based filtering (230) on the BLOBs that groups similar BLOBs and filters away unwanted noise for determining entirety of the BLOBs for each object; and aggregating the groups of BLOBs that belong to the same object (240). The aggregated BLOBs are representations of each object that are individually, and entirely or substantially entirely detected from the images despite having gaps in between the different bodies or spaces, or in between both of the different bodies and spaces on each object. Furthermore, this invention enables multiple objects to be detected from a single image.

Abstract translation: 本公开描述了用于从至少一个图像中检测对象的系统和方法。 这种发明对检测车牌和识别车牌上的字符很有用。 该方法包括以下步骤：在图像上执行基于边缘的技术（210）以识别在二值化图像时潜在地表示对象的二进制大对象（BLOB）; 执行动态膨胀（220），其确定所述对象分别位于其上的不同物体，用于识别出现在单个图像中的不同物体的BLOB; 对组合类似BLOB的BLOB应用基于组的过滤（230）并过滤掉不想要的噪声以确定每个对象的整个BLOB; 并聚合属于同一对象的BLOB组（240）。 聚集的BLOB是每个对象的表示，它们是单独的，并且完全或基本上完全从图像中检测到，尽管在不同物体或空间之间存在间隙，或者在每个对象上的不同物体和空间两者之间存在间隙。 此外，本发明使得能够从单个图像检测多个对象。

公开(公告)号：WO2019066643A3

公开(公告)日：2019-04-04

申请号：PCT/MY2018/050065

申请日：2018-09-28

Applicant: MIMOS BERHAD

Inventor： HUM, Yan Chai ,  MOKAYED, Hamam ,  HON, Hock Woon ,  CHOO, Che Yon ,  BINTI HASAN, Hasmarina

IPC: G06K9/32 ,  G06K9/38

Abstract: The present invention relates to a method for binarising license plate. The method includes the steps of filtering noises in an image of the license plate, correcting the orientation of the image of the license plate, portioning the image of the plate into two pairs of sub-images, computing histograms of pixel intensity for all the sub-images, defining range of interest for each histogram, computing cross-bin histogram similarity measurement, determines whether the similarity measurement is higher than a certain threshold, adapting a local binarisation if the similarity score is higher than the threshold, recognising individual entity of the plate and transforming individual entity of the license plate into the text format of alphabet and number, and analysing all the recognised entity in order to determine the final context of the plate.

公开(公告)号：WO2019066641A3

公开(公告)日：2019-04-04

申请号：PCT/MY2018/050063

申请日：2018-09-28

Applicant: MIMOS BERHAD

Inventor： LIANG, Kim Meng ,  MOKAYED, Hamam ,  HUM, Yan Chai ,  HON, Hock Woon

IPC: G06K9/62

Abstract: The present invention relates to a system (100) and method for recognising license plate. The system (100) comprising an image acquisition module (10) configured to obtain a plurality of continuous frames, a plate detection module (20) configured to detect the location of the license plate inside the plurality of continuous frames, and a plate recognition module (30) configured to recognise and transform content of the license plate image received from the plate detection module (20) into character text format. The system (100) further comprising a post-processing module (40) configured to analyse a plurality of recognised license plates from the plate recognition module (30) using multi-bag analysis to derive a final recognition result from the plurality of recognised license plates by classifying the plurality of recognised license plates based on the length of the recognised license plates and number of identical numeric and alphabet of the recognised license plates.