A Robust Algorithm for Text String Separation from Mixed Text/Graphics Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gray Level Thresholding in Badly Illuminated Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Extraction of binary character/graphics images from grayscale document images
CVGIP: Graphical Models and Image Processing
Page segmentation and classification
CVGIP: Graphical Models and Image Processing
Document image analysis
Evaluation of Binarization Methods for Document Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Document Image Binarization Based on Texture Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
The indexing and retrieval of document images: a survey
Computer Vision and Image Understanding - Special issue on document image understanding and retrieval
Integral Ratio: A New Class of Global Thresholding Techniques for Handwriting Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
TextFinder: An Automatic System to Detect and Recognize Text In Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer and Robot Vision
Image Analysis Applications
Digital Picture Processing
Recognizing Characters in Scene Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Goal-Directed Evaluation of Binarization Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear-time connected-component labeling based on sequential local operations
Computer Vision and Image Understanding
Document page decomposition by the bounding-box project
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
Recursive X-Y cut using bounding boxes of connected components
ICDAR '95 Proceedings of the Third International Conference on Document Analysis and Recognition (Volume 2) - Volume 2
Text Extraction from Gray Scale Document Images Using Edge Information
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Edge-Based Method for Text Detection from Complex Document Images
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Color segmentation for text extraction
International Journal on Document Analysis and Recognition
A Discriminant Analysis Based Recursive Automatic Thresholding Approach for Image Segmentation
IEICE - Transactions on Information and Systems
Adaptive document block segmentation and classification
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A recursive thresholding technique for image segmentation
IEEE Transactions on Image Processing
Stroke-model-based character extraction from gray-level document images
IEEE Transactions on Image Processing
Iterative multimodel subimage binarization for handwritten character segmentation
IEEE Transactions on Image Processing
An intelligent method to extract characters in color document with highlight regions
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II
Expert Systems with Applications: An International Journal
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This study presents a new method, namely the multi-plane segmentation approach, for segmenting and extracting textual objects from various real-life complex document images. The proposed multi-plane segmentation approach first decomposes the document image into distinct object planes to extract and separate homogeneous objects including textual regions of interest, non-text objects such as graphics and pictures, and background textures. This process consists of two stages-localized histogram multilevel thresholding and multi-plane region matching and assembling. Then a text extraction procedure is applied on the resultant planes to detect and extract textual objects with different characteristics in the respective planes. The proposed approach processes document images regionally and adaptively according to their respective local features. Hence detailed characteristics of the extracted textual objects, particularly small characters with thin strokes, as well as gradational illuminations of characters, can be well-preserved. Moreover, this way also allows background objects with uneven, gradational, and sharp variations in contrast, illumination, and texture to be handled easily and well. Experimental results on real-life complex document images demonstrate that the proposed approach is effective in extracting textual objects with various illuminations, sizes, and font styles from various types of complex document images.