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Ashok Kumar, T.
- Localization of Defects in Fabric Imagery Using Contrast Limited Adaptive Histogram Equalization and Mathematical Morphology
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Authors
Affiliations
1 Govt. Model Engineering College, Ernakulam, Kerala, IN
2 College of Engineering, Cherthala, Kerala, IN
3 Department of CS/IT/Research, Toch Institute of Science & Technology, Arakkunnam, Ernakulam, Kerala, IN
4 Dean in PSR Engineering College, Sevalpatti, Sivakasi, Tamilnadu, IN
1 Govt. Model Engineering College, Ernakulam, Kerala, IN
2 College of Engineering, Cherthala, Kerala, IN
3 Department of CS/IT/Research, Toch Institute of Science & Technology, Arakkunnam, Ernakulam, Kerala, IN
4 Dean in PSR Engineering College, Sevalpatti, Sivakasi, Tamilnadu, IN
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Digital Image Processing, Vol 4, No 14 (2012), Pagination: 776-781Abstract
Automated visual inspection systems are a long felt alternative to human visual inspection systems in the textile industry, especially when the quality control of products in the industry is a significant problem. It is observed that the price of textile fabric is reduced by 45% to 65% due to defects. In the manual fault detection systems with trained inspectors, only very few defects are being detected while an automatic system can increase this to a maximum number thus, automated visual inspection systems play a great role in assessing the quality of textile fabrics. For the detection of defects in a homogeneous fabric, we first perform bit plane decomposition of the image. The lower order bit planes are found to be useful for the localization of defects while eliminating the prints and other parts. Then we extract the exact boundary by means of mathematical morphology. The algorithm has been evaluated on a subset of TILDA1 image database with various visual qualities. Robustness with respect to the changes of the parameters of the algorithm has been examined.Keywords
Adaptive Histogram Equalization, Bit Plane Decomposition, Image Processing, Mathematical Morphology, Fabric Defects, Top-Hat Transform, Bottom-Hat Transform.
- Fast Optic Disc Localization and Extraction in Retinal Fundus Images Using Bitplane Decomposition and Mathematical Morphology
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Authors
Affiliations
1 College of Engineering (A Govt. of Kerala Undertaking), Cherthala, Kerala, IN
2 Govt. Model Engineering College, Thrikkakara, Ernakulam, Kerala, IN
3 Department of Electronics Engineering, Govt. Model Engineering College, Thrikkakara, Ernakulam, Kerala, IN
1 College of Engineering (A Govt. of Kerala Undertaking), Cherthala, Kerala, IN
2 Govt. Model Engineering College, Thrikkakara, Ernakulam, Kerala, IN
3 Department of Electronics Engineering, Govt. Model Engineering College, Thrikkakara, Ernakulam, Kerala, IN
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Digital Image Processing, Vol 3, No 3 (2011), Pagination: 149-154Abstract
This paper presents an approach to the fast localization and extraction of optic disc from fundus images of the human retina. For the diagnosis of Diabetic Retinopathy and other eye related abnormalities, digital fundus images are becoming increasingly important. This fact opens the possibility of applying image processing techniques in ocular fundus images to facilitate and improve diagnosis in different ways. Optic disc is the major landmark for retinal fundus image registration and is indispensible for the quick understanding of retinal images. For the detection and subsequent extraction of optic disc, we first perform bit plane decomposition to the image. The lower order bit planes are found to carry vital information of the location and boundary of optic disc. Then we locate the exact boundary by means of mathematical morphology. The algorithm has been evaluated on a subset of MESSIDOR1 image database with various visual qualities. Robustness with respect to the changes of the parameters of the algorithm has been examined.Keywords
Bit Plane Decomposition, Image Processing, Mathematical Morphology, Optic Disc Localization.- Classification of Remote Sensed Data Using Hybrid Method Based on Ant Colony Optimization with Electromagnetic Metaheuristic
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Authors
Affiliations
1 Department of Electronics and Communication Engineering, GSSS Institute of Engineering and Technology for Women, Mysuru 570 016, IN
2 Department of Electronics and Communication Engineering, ATME College of Engineering, Mysuru 570 028, IN
3 PES Institute of Technology and Management, Shivamogga 577 204, IN
4 Department of Electronics and Communication Engineering, Malnad College of Engineering, Hassan 573 202, IN
1 Department of Electronics and Communication Engineering, GSSS Institute of Engineering and Technology for Women, Mysuru 570 016, IN
2 Department of Electronics and Communication Engineering, ATME College of Engineering, Mysuru 570 028, IN
3 PES Institute of Technology and Management, Shivamogga 577 204, IN
4 Department of Electronics and Communication Engineering, Malnad College of Engineering, Hassan 573 202, IN
Source
Current Science, Vol 113, No 02 (2017), Pagination: 284-291Abstract
In this study, a hybrid configuration of electromagnetic metaheuristic algorithm (EM) with Pachycondyla apicalis (API) ant algorithm (inspired by the behaviour of real ant colony Pachycondyla apicalis) belonging to ant colony optimization (ACO) called EMAPI algorithm is presented for remote sensing data classification. The traditional per-pixel classification method identifies the classes using spectral variance and ignores the spatial distribution of pixels. It requires training data to be normally distributed in the pixels corresponding to land use/land cover classes and creates a lot of confusion between classes within a remote sensed (RS) data. The proposed algorithm is an integrated strategy structure to achieve advantages of global and local search ability of EM and API algorithms respectively. The objective consists of improving overall accuracy of the classified results of RS data. This method can overcome intermixing with regard to scrub land with cultivated areas and build-up land with palm groves. The proposed algorithm is tested on objective functions well used in the literature and EMAPI is used for supervised land cover classification. Results of EMAPI algorithm over 6 classes showed an improvement of 8% in overall classification accuracy (OCA) for EM technique and improvement of 3% in OCA for API algorithm.Keywords
Ant Colony Optimization, API Algorithm, Electromagnetic Metaheuristic, Data Classification, Hybrid Metaheuristic.Full Text
References
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- Bardossy, A. and Samaniego, L., Fuzzy rule-based classification of remotely sensed imagery. IEEE Trans. Geosci. Remote Sensing, 2002, 40(2), 362–374; doi:10.1109/36.992798.
- Shankar, B. U., Saroj, K. and Ashish, G., Wavelet-fuzzy hybridization: feature-extraction and land-cover classification of remote sensing images. Appl. Soft Comput., 2011, 11, 2999–3011; doi:10.1016/j.asoc.2010.11.024.
- Giacinto, G., Roli, F. and Bruzzone, L., Combination of neural and statistical algorithms for supervised classification of remotesensing images. Pattern Recognit. Lett., 2000, 21, 385–397; doi:10.1016/S0167-8655(00)00006-4.
- Du, P., Tan, K. and Xing, X., A novel binary tree support vector machine for hyperspectral remote sensing image classification. Opt. Commun., 2012, 285, 3054–3060; doi:10.1016/j.optcom.2012.02.092.
- Zheng, J., Cui, Z., Liu, A. and Jia, Y., A K-means remote sensing image classification method based on adaboost. natural computation. ICNC ’08. 2008, vol. 4, pp. 27–32; doi:10.1109/ICNC.2008.903.
- Jayanth, J., Ashok Kumar, T. and Shiva Prakash Koliwad, Assessing different change detection technique to detect land cover changes in coastal region of Mangalore. Int. J. Earth Sci. Eng., 2014, 7(5), 1696–1703.
- Jayanth, J., Ashok Kumar, T., Shiva Prakash Koliwad and Srikrishnashastry, Identification of land cover changes in the coastal area of Dakshina Kannada district, south India, during the year 2004–2008. Egyptian J. Remote Sensing Space Sci., 2016, 117–128 (EJRS, ISSN:1110-9823).
- Yang, H., Du, Q. and Chen, G., Particle swarm optimization-based hyperspectral dimensionality reduction for urban land cover classification. IEEE J. Sele Topics Appl. Earth Observ. Remote Sensing, 2012, 5(2), 544–554; doi:10.1109/JSTARS.2012.2185822.
- Liu, X., Li, X., Liu, L. and Ai, B., An innovative method to classify remote-sensing images using ant colony optimization. IEEE Trans. Geosci. Remote Sensing, 2008, 46(12), 24–28; doi:10.1109/TGRS.2008.2001754.
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- Dorigo, M. and Blumb, C., Ant colony optimization theory: A survey. Theor. Comput. Sci., 2005, 344, 243–278; doi:10.1016/j.tcs.2005.05.020.
- Jayanth, J., Koliwad, S. and Ashok Kumar, T., Classification of remote sensed data using artificial bee colony algorithm. Egyptian J. Remote Sensing Space Sci., 2015, 119–126; doi:10.1016/j.ejrs.2015.03.001.
- Ciornei, I. and Kyriakides, E., Hybrid ant colony-genetic algorithm (gaapi) for global continuous optimization. IEEE Trans. Systems. Man. Cybernetics – Part B, 2012, 42(1), 234–245; doi: 10.1109/TSMCB.2011.2164245.
- Zhong, Y., Zhang, L., Huang, B. and Li, P., An unsupervised artificial immune classifier for multi/hyperspectral remote sensing imagery. IEEE Trans. Geosci. Remote Sensing, 2006, 44(2), 420–431; doi:10.1109/TGRS.2005.861548.
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- Densification and Deformation Behaviour of Sintered P/M AL-C-CU-MG Alloys During Cold Upsetting
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Affiliations
1 School of Mechanical Engineering, Shanmugha Arts, Science, Technology & Research Academy (SASTRA), Deemed University, Thanjavur-613402, Tamil Nadu, IN
1 School of Mechanical Engineering, Shanmugha Arts, Science, Technology & Research Academy (SASTRA), Deemed University, Thanjavur-613402, Tamil Nadu, IN
Source
Manufacturing Technology Today, Vol 5, No 7 (2006), Pagination: 5-8Abstract
The present investigation is focused on the densification behaviour of sintered aluminium alloys of AI-Cu-C with additions of magnesium powder in varying quantities. The influence of normalizing heat treatment on deformation behaviour has also been investigated. Magnesium powder (-150 μ) has been added in varying percentage to Al-Cu-C alloy phase in order to study the influence of Mg on the deformation, densification and metallurgical structure of the P/M Al alloys mentioned above. Elemental powders of Al, Mg, C &Cu were mixed thoroughly in a pot mill for 8 hrs and the powder blends were compacted In to cylindrical shaped preforms of aspect ratio 0.6, applying a pressure of 125 MPa. in hydraulic press. After sintering at 550 °C for 90 minutes cold upsetting tests were carried out on the preforms. Another set of cold upsetting tests were undertaken after subjecting the sintered preforms to normalizing heat treatment at 500 °C. Density and dimensional measurements were carried out after each step of deformations. Axial upsetting was continued upto the point of appearance of fine surface cracks on the bulged surfaces. The results of the investigations revealed that the normalizing heat treatment notably Influenced the flow stress of the alloys. However It has marginal effects on densifications. Addition of higher percentage of Mg to Al-1% C-1% Cu alloy has also affected the deformation as well as densification behavior. Increasing the Mg content has lead to reduced levels of plastic deformation as well as densification. The combination o f addition of Mg and heat treatment has Influenced the flow stress because adding higher Mg demands higher flow stresses during axial upsetting. Normalizing of the alloys with Mg content enhances the resistance to deformation and densification. Addition of Mg to the alloy AI-C-Cu has reversed the response of the material during cold upsetting. The microstructure of the alloys reveals the presence of numerous rounded and small pores with in the grains and along the grain boundary. It also reveals subtle differences due to normalizing heat treatment.- Cold Deformation Studies on P/M AL-C-CU-FE Alloys
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Authors
Affiliations
1 School of Mechanical Engineering, Shanmugha Arts, Science, Technology & Research Academy (SASTRA), Deemed University, Thanjavur-613402, Tamil Nadu, IN
1 School of Mechanical Engineering, Shanmugha Arts, Science, Technology & Research Academy (SASTRA), Deemed University, Thanjavur-613402, Tamil Nadu, IN
Source
Manufacturing Technology Today, Vol 5, No 5 (2006), Pagination: 11-15Abstract
Aluminium based MMC's with SiC reinforcement are known to find numerous applications in the aerospace and automotive industry In view of high strength to weight ratio and stiffness. Alloys with Cu, Zn, Mg added to Al are also high strength light weight materials widely used in aerospace industry for application such as landing gears, fasteners etc,. In the present investigation atomized iron powder has been added In varying percentages to Al-Cu-C alloy phase in order to study the influence of Fe on deformation, densification and metallurgical structure of sintered Al alloys. Elemental powders of Al, Fe, C & C u were mixed thoroughly In a pot mill for 8 hrs and the powder blends were compacted in to cylindrical shaped performs of aspect ratio 0.6. After sintering at 550°C for 90 minutes cold upsetting test were carried out in the performs. Another set of cold upsetting test were undertaken after subjecting the sintered preforms to normalizing heat treatment at 500°C. Density and dimensional measurements were carried out after each step of deformation level. The results of the investigations revealed that the normalizing heat treatment notably influenced the flow stress of the alloys. However it has only marginal effects on densification. Addition of Fe to AI-1% C-1%Cu alloys in the proportion of 0.1, 0.2, and 0.3 has also affected the deformation as well as densification behavior. Increasing the Fe content has lead to reduced levels of plastic deformation as well as densification. The combined effects of addition of Fe and heat treatment have affected the flow stress. Adding higher Fe contents demands higher flow stress. Normalizing of the alloys with Fe contents enhances the resistance to deformation and densification. The stress-strain behavior in all the cases of the alloys is characterized by linearity. The peak density levels achieved after the forging not exceed 96% of theoretical density. The microstructure of the alloys reveals the presence of numerous rounded and small pores within the grains and along the grain boundary.- Scheme for Fabricating an Adaptive Controlled Parallel Stewart Type Robot for High Precision Accuracies
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Authors
Affiliations
1 School of Mechanical Engineering, SASTRA, Deemed University, Thanjavur-613402, IN
1 School of Mechanical Engineering, SASTRA, Deemed University, Thanjavur-613402, IN
Source
Manufacturing Technology Today, Vol 5, No 3 (2006), Pagination: 20-22Abstract
The Stewart platform is well known parallel robotic mechanism often used as a flight simulator. Less well known applications Involve robotics and machine tools. In recent years there is a considerable interest in the application of parallel robots because of their greater stiffness and accuracy when compared to the standard serial robots. The most industrial robot manipulators have serial link chains that have characteristics of wide workspace, low stiffness. Error accumulation in end effector’s pose is mainly due to open loop kinematic structures. Therefore the serial link manipulators are not suitable for high speeid and high accurate positioning operations. During the last decade, parallel manipulators have been designed, analyzed and constructed in order to overcome those disadvantages by utilizing high stiffness and low error accumulation characteristics of closed loop kinematic structure. The end effector loads are distributed to simple compression - tension loads among the parallel links so that the bending deformation is not induced. In medical field, parallel robots play a vital role in accurate remote manipulation of a laparoscopic laser dissection tool. Laparoscope’s surgery has gained increasing popularity in recent years and many operative procedures are nowadays performed by this minimaliy invasive approach, requiring fine dexterity and accurate microsurgical technique. However there are some drawbacks in parallel manipulators such as small workspace and very complex dynamics due to dosed chain structure. Therefore it is in general more difficult to control parallel manipulators. Present use of industrial robot is concentrated in rather simple, repetitive tasks, which tend not to require high precision. Manufacturing market analysis predict that in the 2000’s industriaL robots will become increasingly viable in applications which require more precision and sensory sophistication such as machining, medical operations, assembly tasks etc.,. So to have high precision and accuracy parallel robot concept is inevitable.- Fusion of Multispectral and Panchromatic Data using Regionally Weighted Principal Component Analysis and Wavelet
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Authors
Affiliations
1 Department of Electronics and Communication Engineering, GSSS Institute of Engineering and Technology for Women, Mysuru 570 016,, IN
2 SDM Institute of Technology, Ujire, Belthangady 574 240, IN
3 Department of Electronics and Communication Engineering, Malnad College of Engineering, Hassan 573 202, IN
1 Department of Electronics and Communication Engineering, GSSS Institute of Engineering and Technology for Women, Mysuru 570 016,, IN
2 SDM Institute of Technology, Ujire, Belthangady 574 240, IN
3 Department of Electronics and Communication Engineering, Malnad College of Engineering, Hassan 573 202, IN
Source
Current Science, Vol 115, No 10 (2018), Pagination: 1938-1942Abstract
This study proposes a new multispectral (MS) and panchromatic (PAN) image fusion algorithm based on regionally weighted principal component analysis (RW-PCA) and wavelet. First, the MS images are segmented into spectrally similar regions based on the fuzzy c-means (FCM) clustering method. Secondly, based on the spectral vector’s degree of membership in each region, a new RW-PCA method is proposed to fuse the MS and PAN images region by region, and fused MS images are obtained. In the traditional PCA-based fusion method, the MS and PAN images are fused globally with the same transform method. In the proposed RW-PCA-based fusion method, the local spectrum information of the MS images is employed, and the spectral information is better preserved in the fused MS images. Finally, in order to improve the quality of spectral and spatial details, the above fused MS images and the original PAN images are further fused using the wavelet-based fusion method, and the final fused MS images are obtained. Experimental results demonstrated that the proposed image fusion algorithm performs better in spectral preservation and spatial quality improvement than some other methods do.Keywords
Fuzzy, RWPCA_WT, Regionally Weighted, WT.Full Text
References
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- Jayanth J, Ashok Kumar, T. and Shiva Prakash Koliwad, Comparative analysis of image fusion techniques for remote sensing. International Conference on Advanced Machine Learning Technologies and Applications (AMLTA 2012) Cairo, Egypt, 8–10 December 2012. Proc. Commun. Comput. Inf. Sci. (eds Hassanien, A. E. et al.), Springer, Berlin/Heidelberg, Germany, 2012, 322, 111–117.
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- Jayanth, J., Ashok Kumar, T. and Shiva Prakash Koliwad, Image fusion using DWT + IHS for coastal region change detection. Proceedings of the International Conference Current Trends Engineering Management (ICCTEM), 12–14 July 2012, VVCE, Mysore, Karnataka, India, pp. 26–31.
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- Jayanth, J. Ashok Kumar, T. and Shiva Prakash Koliwad, Six different image fusion techniques for remote sensed data. Proceedings of the International Conference on Communication, VLSI and Signal Processing (ICCVSP), 20–22 February 2013, SIT, Tumkur, India, pp. 22–25.
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