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。