Therefore, this paper would review the research related to the scene text detection process in the last ten years. The success of text recognition starts with the ability of the system to detect the presence of text in the scene image.
The road signs recognition, the input of images on machine translation, the text recognition on commercial products, billboards, or vehicle plates are some examples of the use of text recognition on natural images. The rapid development of scene text detection shows the need for text recognition in a scene image. The benefit of text analysis on Aksara Jawa. Text confidence map is then produced followed by boundingīoxes formation which is estimated and formed to indicate the Technique is employed to obtain parameters simultaneously. This method are jointly learned from which the back-propagation This method mainly differs from the existingĪksara Jawa text works that employ manually hand-crafted features and explicitly learn a classifier. Preserving and converting visual information into text, we developĪksara Jawa text detection system in scene images employingĭeep convolutional neural network to localize the occurrence ofĪksara Jawa text.
Thus, it is extremely important to preserve Written on stones to describe history or naming such as places, Aksara jawa is an ancient Javanese character,
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