Text extraction from color map images

Abstract

Separation of characters and lines in color map images, especially when they are connected or overlapped, is a very challenging task in image analysis. We present a method to tackle this problem using robust ilne tracing, connected component analysis, and color clustering algorithms. Good results have been obtained using this method with real test images.

Deep-Learning-Based Annotation Extraction Method for Chinese Scanned Maps

“…This indicates the potential of the suggested model to deliver successful outcomes in the domain. (2) The CRNN annotation recognition model based on transfer learning proposed in this article achieved scores of 0.9320, 0.8956, and 0.9134 for precision, recall, and h mean,…”

“…2023, 12, 422 2 of 20 Some researchers have suggested a technique where annotations are first identified within maps using computer technology, followed by manual interpretation and conversion, in order to minimize the need for human participation. In the early stages of map annotation localization, techniques such as cluster analysis [2], morphological operations [3], segmentation [4], labeling connected components [2] and the use of image pyramid methods have been used [5]. Even though these techniques are capable of automatically locating map annotations, the extraction of such annotations is less precise when they are intertwined and overlapped with other elements on the map.…”

Back Matter

“…Shannon's entropy function, 59 unsupervised pattern recognition method, sigmoidal transfer function, 42 …”