Efficient multiscale Sauvola’s binarization Lazzara, Guillaume; Géraud, Thierry
International journal on document analysis and recognition,
2014/6, Volume:
17, Issue:
2
Journal Article
Peer reviewed
Open access
This work focuses on the most commonly used binarization method: Sauvola’s. It performs relatively well on classical documents, however, three main defects remain: the window parameter of Sauvola’s ...formula does not fit automatically to the contents, it is not robust to low contrasts, and it is not invariant with respect to contrast inversion. Thus, on documents such as magazines, the contents may not be retrieved correctly, which is crucial for indexing purpose. In this paper, we describe how to implement an efficient multiscale implementation of Sauvola’s algorithm in order to guarantee good binarization for both small and large objects inside a single document without adjusting manually the window size to the contents. We also describe how to implement it in an efficient way, step by step. This algorithm remains notably fast compared to the original one. For fixed parameters, text recognition rates and binarization quality are equal or better than other methods on text with low and medium x-height and are significantly improved on text with large x-height. Pixel-based accuracy and OCR evaluations are performed on more than 120 documents. Compared to awarded methods in the latest binarization contests, Sauvola’s formula does not give the best results on historical documents. On the other hand, on clean magazines, it outperforms those methods. This implementation improves the robustness of Sauvola’s algorithm by making the results almost insensible to the window size whatever the object sizes. Its properties make it usable in full document analysis toolchains.
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This paper presents a practical human-computer interaction system for wheelchair motion through eye tracking and eye blink detection. In this system, the pupil in the eye image has been extracted ...after binarization, and the center of the pupil was localized to capture the trajectory of eye movement and determine the direction of eye gaze. Meanwhile, convolutional neural networks for feature extraction and classification of open-eye and closed-eye images have been built, and machine learning was performed by extracting features from multiple individual images of open-eye and closed-eye states for input to the system. As an application of this human-computer interaction control system, experimental validation was carried out on a modified wheelchair and the proposed method proved to be effective and reliable based on the experimental results.
In bearing diagnostics using a data-driven modeling approach, a concern is the need for data from all possible scenarios to build a practical model for all operating conditions. This paper is a study ...on bearing diagnostics with the concurrent occurrence of multiple defect types. The authors are not aware of any work in the literature that studies this practical problem. A strategy based on one-versus-all (OVA) class binarization is proposed to improve fault diagnostics accuracy while reducing the number of scenarios for data collection, by predicting concurrent defects from training data of normal and single defects. The proposed OVA diagnostic approach is evaluated with empirical analysis using support vector machine (SVM) and C4.5 decision tree, two popular classification algorithms frequently applied to system health diagnostics and prognostics. Statistical features are extracted from the time domain and the frequency domain. Prediction performance of the proposed strategy is compared with that of a simple multi-class classification, as well as that of random guess and worst-case classification. We have verified the potential of the proposed OVA diagnostic strategy in performance improvements for single-defect diagnosis and predictions of BPFO plus BPFI concurrent defects using two laboratory-collected vibration data sets.
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Combinatorial patterns of histone modifications sketch the epigenomic locale. Specific positions of these modifications in the genome are marked by the presence of such signals. Various methods ...highlight such patterns on global scale hence missing the local patterns which are the actual hidden combinatorics. We present ChromBiSim, an interactive tool for mining subsets of modifications from epigenomic profiles. ChromBiSim efficiently extracts biclusters with their genomic locations. It is the very first user interface based and multiple cell type handling tool for decoding the interplay of subsets of histone modifications combinations along their genomic locations. It displays the results in the forms of charts and heat maps in accordance with saving them in files which could be used for post analysis.
ChromBiSim tested on multiple cell types produced in total 803 combinatorial patterns. It could be used to highlight variations among diseased versus normal cell types of any species.
ChromBiSim is available at (http://sourceforge.net/projects/chrombisim) in C-sharp and python languages.
•ChromBiSim is an interactive GUI based tool.•It is the very first unsupervised biclustering tool for mining histone modifications combinations.•It mines all possible combinations of histone modifications and is based on binarization approach.•Useful for comparative analysis of epigenomic profiles based on present signals of histone modifications.
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The efficiency of using Zernike moments when working with digital images obtained in the infrared region of the spectrum is considered to improve the accuracy and speed of an autonomous thermal ...imaging system. The theoretical justification of the choice of Zernike moments for solving computer (machine) vision problems and the choice of a suitable threshold binarization method is given. In order to verify the adequacy and expediency of using the chosen method, practical studies were conducted on the use of Zernike methods for distorting various thermal images in shades of gray.
The content of this work is based on the characteristics of standard artificial bee colony(ABC) algorithm with weak local search ability and slow convergence speed. Then, an improved algorithm named ...KD-ABC is proposed. For improving the diversity and quality of the solution, it changes the generation method of honey source. In the initialization phase, it uses the cluster center generated by the K-MEANS method as the initial honey source instead of the initialization in the standard method. For improving the local optimization ability and the convergence speed without reducing the global search, we proposed a dynamic neighborhood search mechanism based on the number of iterations in terms of ABC search strategy and neighborhood selection stage. In order to find a suitable threshold to divide the grayscale image into blood vessels and background parts, we applied the characteristics of the KD-ABC algorithm to the binary processing stage of the fundus retinal blood vessel image, which lays the foundation for future image recognition.
This paper presents the results of tomography studies of a porous ceramic–metal membrane based on coarse-grained aluminum oxide. For the development of a technology for the manufacturing of ...ceramic–metal membranes with specified properties by the method of self-propagating high-temperature synthesis, it is important to have information about the internal morphological structure of the membrane, which determines such characteristics as the porosity, specific surface area, etc. A closer look at the data of X-ray computed microtomography (µCT) would allow one to study the effect of the technological-process parameters on the morphology of the membrane and, consequently, on its properties. Tomographic measurements of the membrane are carried out using an original laboratory setup. It is shown for the first time that single-pixel pores and “levitating stones” have an effect on the calculated characteristics of the membranes. We use this fact in our data-processing strategy. The morphological characteristics are calculated from the results of tomographic reconstruction after the filtration of noise and binarization by Otsu’s method. Comparison of the values of the morphological characteristic calculated from the binarized reconstructed image with the results of measurements by other methods shows good agreement in the magnitudes of the porosity and pore size and a difference in the values of the specific surface area, which can be explained by a discrepancy in the spatial resolution of the employed methods.
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•A solution of skin cancer pattern recognition using fractal methods on multispectral images is proposed.•Lacunarity and box dimension is used to get the pattern characteristic.•Multiple image ...binarization methods are tested together with different classification methods.•Proposed solution shows that fractal methods can be combined with binarization methods for some skin cancer patterns.
Melanoma is widely known as one of the most dangerous cancers. Over the past few decades, technological improvements have made it possible to introduce more advanced diagnostic tools for melanoma. Unfortunately, even though better tools are available, diagnosis accuracy is still unsatisfactory. Hundreds of papers have been published containing ideas on how to improve melanoma diagnosis accuracy, including a range of imaging and image analysis techniques. Some of the best diagnosis results are obtained using multi-level SIAscope images, but even with this method there is still room for further improvement. In this paper, we propose the use of additional discriminative features such as box dimension and lacunarity calculated based on a multilevel image database. The goal of this paper is to show the usefulness of fractal methods used with multilevel images and binarization methods in skin cancer pattern recognition. The results were compared to an assessment of each feature of Hunter’s scoring method, which is commonly used as a diagnostic indicator by doctors. The results indicate the usefulness of the fractal characteristics of the geometric shapes of lesions or specific parts of them. Compared to other research, the presented results clearly indicate that fractal lesion characteristics can be used as one of the features taken into account in the diagnostic process.
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Document image binarization involves converting gray level images into binary images, which is a feature that has significantly impacted many portable devices in recent years, including PDAs and ...mobile camera phones. Given the limited memory space and the computational power of portable devices, reducing the computational complexity of an embedded system is of priority concern. This work presents an efficient document image binarization algorithm with low computational complexity and high performance. Integrating the advantages of global and local methods allows the proposed algorithm to divide the document image into several regions. A threshold surface is then constructed based on the diversity and the intensity of each region to derive the binary image. Experimental results demonstrate the effectiveness of the proposed method in providing a promising binarization outcome and low computational cost.
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