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1
Map image binarization and stitching using extraction of regions
Mandal S., Biswas S., Das A. K, Chanda B.
Journal of Theoretical and Applied Computer Science
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2015
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Vol. 9, nr 1
28--40
EN
Binarisation methods already reported are inadequate for binarisation of complex documents such as maps due to large intensity variations across the regions and entangled texts with lines representing borders, rivers, roads and similar other components. This paper proposes a new binarisation technique for coloured land map images by extracting the regions and analysing the hue, saturation spread and within class kurtosis. This is a region-wise adaptive algorithm to cope up with the sharp changes of the discriminating features across different regions. Here, local regions are selected as clusters having the same hue and saturation. The regions are individually binarised using the spread of their degree of within class kurtosis and finally combined together. The regions extracted are further utilised for stitching of map documents which contain some portion in common. We use a simple greedy technique using correlation matching to join two or more map images such that information from both can be viewed and compared. Our experiments include 446 colour maps from the map image database created for this purpose and made freely available at website. This work is an extended version of our previous work on map image binarisation [1].
2
Content available remote Text Segmentation from Bangla Land Map Images
Biswas S., Das A. K, Chanda B.
Image Processing & Communications
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2014
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Vol. 19, no. 1
21--34
EN
Text segmentation from land map images is a non-trivial task as map components are interleaved and overlapped in a complex spatial form. The characters in a word in most of the Indic languages, including Bangla (the 6th most spoken language in the world), are connected through a headline (”matra” or ”shirorekha”) which makes the corresponding word a single component. It has been observed that the Delaunay triangulation (DT) forms a number of small triangles on the text regions compared to other regions of the map - a property very much discernible for Bangla (and some other Indic scripts) texts. This property is primarily exploited here to segment text from the complex background of the land map images. The proposed text segmentation approach is tested and compared with an existing method on a collected dataset of paper map images( containing Bangla, an Indian regional language texts) and the results are encouraging.
3
Content available remote Land Map Image Dataset: Ground-Truth And Classification Using Visual And Textural Features
Mandal S., Biswas S., Kumar-Das A., Chanda B.
Image Processing & Communications
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2014
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Vol. 19, no. 4
37--55
EN
Research on document image analysis is actively pursued in the last few decades and services like OCR, vectorization of drawings/graphics and various types of form processing are very common. Handwritten documents, old historical documents and documents captured through camera are now being the subjects of active research. However, another very important type of paper document, namely the map document image processing research suffers due to the inherent complexities of the map document and also for nonavailability of benchmark public data-sets. This paper presents a new data-set, namely, the Land Map Image Database (LMIDb) that consists of a variety of land maps images (446 images at present and growing; scanned at 200/300 dpi in TIF format) and the corresponding ground-truth. Using semiautomatic tools non-text part of the images are deleted and the text-only ground-truth is also kept in the database. This paper also presents a classification strategy for map images using which the maps in the database are automatically classified into Political (Po), Physical (Ph), Resource (R) and Topographic (T) maps. The automatic classification of maps help indexing of the images in LMIDb for archival and easy retrieval of the right maps to get the appropriate geographical information. Classification accuracy is also tested on the proposed data-set and the result is encouraging.
4
Content available remote A video coding technique with BTC-PF method for fast decoding
Dhara B. C., Saha S. K., Chanda B.
Image Processing & Communications
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2011
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Vol. 16, no 1-2
29-42
EN
We have presented a video coding system that enables fast decoding and there by caters the need of the real time applications like video on demand, video play back, video retrieval. Proposed methodology relies on a fast motion estimation scheme, hierarchical BTC-PF based redundancy removal technique and finally it uses entropy decoding. As the encoding method is free from transformation and quantization steps, the decoding becomes faster. It also maintains the quality within the acceptable limit and improves bpp.
5
Content available remote Extraction, representation and analysis of geographical spatial information from topographic paper maps
Dhar D. B., Chanda B.
Image Processing & Communications
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2010
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Vol. 15, no 1
5-22
EN
Emergence of Geographical Information Systems (GIS) has facilitated map acquisition and utilization to a great extent. This paper presents novel methodology for the extraction, representation and analysis of objects and symbols from topographic sheet that are geographically important as well as their spatial interrelationship. The method exploits various image processing tools suitable for specific objects and symbols on the basis of their geometrical and morphological attributes. The output is presented as a spatial database for further query processing and hence is suitable for GIS applications. The methodology is found to perform quite satisfactorily.
6
Content available remote Second Order Fuzzy Measure and Weighted Co-Occurrence Matrix for Segmentation of Brain MR Images
Maji P., Kundu M.K., Chanda B.
Fundamenta Informaticae
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2008
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Vol. 88, nr 1-2
161-176
EN
A robust thresholding technique is proposed in this paper for segmentation of brain MR images. It is based on the fuzzy thresholding techniques. Its aim is to threshold the gray level histogram of brain MR images by splitting the image histogram into multiple crisp subsets. The histogram of the given image is thresholded according to the similarity between gray levels. The similarity is assessed through a second order fuzzy measure such as fuzzy correlation, fuzzy entropy, and index of fuzziness. To calculate the second order fuzzy measure, a weighted co-occurrence matrix is presented, which extracts the local information more accurately. Two quantitative indices are introduced to determine the multiple thresholds of the given histogram. The effectiveness of the proposed algorithm, along with a comparisonwith standard thresholding techniques, is demonstrated on a set of brain MR images.
7
Content available remote Removal of noise from sodar data using ABL characteristics guided morphological filter
Pal P., Mukherjee A., Chanda B.
Image Processing & Communications
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2007
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Vol. 12, no 1
5-15
EN
There is potential of using acoustic sounder system to study boundary layer meteorology. The repeatable patterns on sodar-images become necessary and useful to find suitable techniques for computer analysis and interpretation. Image processing and pattern recognition approaches have been explored for SODAR signal processing. Like all real digital images, sodar-images are also degraded with noise, thereby complicating the sodar-patterns. Since the exact mathematical model of the system is not available, challenges exist to minimise the effect of noise present in the sodar-images. This will lead to better extraction of the sodar-patterns from the sodar-images. Noise cleaning algorithm for sodar-images have been considered here based on the morphology of ABL pattern characteristics. The results of this algorithm compare favourably with the existing methods.
8
Content available remote An initialization-free clustering technique based on symmetry
Pal P., Chanda B.
Image Processing & Communications
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2007
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Vol. 12, no 2
17-25
EN
In this paper we propose a clustering technique that extracts sub-clusters based on a simple measure of isotropic symmetry. These sub-clusters are then used as building blocks to form final clusters of any arbitrary shape including concave ones through merging iteratively. The proposed method is tested on multi-spectral satellite imagery and a good result is obtained. Major advantages of this method are its simplicity and being free from initial guess about the cluster centres, shapes and the number of clusters. However, this algorithm is more suitable for mul-tivariate images even with very high spectral resolution.
9
Content available remote Automatic selection of structuring element for object classification through morphology
Chanda B., Bhattacharyya R.
Image Processing & Communications
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1999
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Vol. 5, no 1
67-79
EN
How to select a structuring element for a given task is one of the most frequently asked questions in morphology. Present work tries to give a solution for a restricted class of problems, namely shape classification. In this work an algorithm that extracts distinctive structure of each of a given set of objects is proposed. The proposed algorithm is based on a new approach for computing distance transform.
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