open access

SCENE TEXT RECOGNITION IN IMAGES BY CHARACTER STRUCTURE CONFIGURATION AND DESCRIPTOR

  • DINESHKUMAR K Assistant Professor,Department of Computer Science and Engineering, Sri K .S .R College of Engineering, Namakkal, Tamil Nadu-637 215, India
  • KUMARESAN K Assistant Professor,Department of Computer Science and Engineering, Sri K .S .R College of Engineering, Namakkal, Tamil Nadu-637 215, India
  • SENTHILKUMAR V Assistant Professor,Department of Computer Science and Engineering, Sri K .S .R College of Engineering, Namakkal, Tamil Nadu-637 215, India
  • KUBENDRAN S Student,Department of Computer Science and Engineering, Sri K .S .R College of Engineering, Namakkal, Tamil Nadu-637 215, India
  • LINGESH G Student,Department of Computer Science and Engineering, Sri K .S .R College of Engineering, Namakkal, Tamil Nadu-637 215, India
  • PASUPATHI M Student,Department of Computer Science and Engineering, Sri K .S .R College of Engineering, Namakkal, Tamil Nadu-637 215, India
  • PRAVEEN K Student,Department of Computer Science and Engineering, Sri K .S .R College of Engineering, Namakkal, Tamil Nadu-637 215, India

Abstract

Camera-Based text information serves as effective tags or clues for many mobile applications associated with media analysis, content retrieval, scene understanding, and assistant navigation. In natural scene images, text characters and strings usually appear in nearby sign boards and provide significant knowledge of surrounding environment and objects. Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, the previously proposed algorithms are applied to obtain text regions from scene image. The paper designs a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, it models character structure at each character class by designing stroke configuration maps. The design is compatible with the application of scene text extraction in images. The system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects.

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