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A Two Stage Method for Bengali Text Extraction from Still Images Containing Text

机译:从包含文本的静止图像中提取孟加拉文本的两阶段方法

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摘要

Bengali text data present in multimedia images having multiple content forms, such as still images and text, contain information that when extracted finds a lot of applications. The images can be of different types, where objects and text may be completely separated or overlapped or embedded in each other. The Bengali text can be of different shapes and sizes. Extraction of text from these types of images becomes challenging because the textual portion has to be correctly separated from the rest of the background. The input image passes through two stages. The first step tries to locate the different components in the image using entropy filtering and the second stage distinguishes the components representing text from the non-textual components based on several features of Bengali text. The text thus obtained from the image can then be used in software such as Bengali OCR for character recognition.
机译:存在于具有多种内容形式的多媒体图像中的孟加拉文本数据(例如,静止图像和文本)包含的信息在提取时具有很多用途。图像可以是不同的类型,其中对象和文本可以完全分开或重叠或彼此嵌入。孟加拉语文本可以具有不同的形状和大小。从这些类型的图像中提取文本变得具有挑战性,因为文本部分必须与背景的其余部分正确分开。输入图像经过两个阶段。第一步尝试使用熵过滤来定位图像中的不同成分,第二步基于孟加拉语文本的多个特征,将代表文本的成分与非文本成分区分开。从图像中获得的文本然后可以在诸如Bengali OCR之类的软件中用于字符识别。

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