Scene Classification using Localized Histogram of Oriented Gradients Method
Scene classification is an important and elementary problem in image understanding. It deals with large number of scenes in order to discover the common structure shared by all the scenes in a class. It is used in medical science (X-Ray, ECG and Endoscopy etc), criminal detection, gender classification, skin classification, facial image classification, generating weather information from satellite image; identify vegetation types, anthropogenic structures, mineral resources, or transient changes in any of these properties. In this paper, at first we propose a feature extraction method named LHOG or Localized HOG. We consider that an image contains some important region which helps to find similarity with same class of images. We generate local information from an image via our proposed LHOG method. Then by combing all the local information we generate the global descriptor using Bag of Feature (BoF) method which is finally used to represent and classify an image accurately and efficiently. In classification purpose, we use Support Vector Machine (SVM) that analyze data and recognize patterns. The basic SVM takes a set of input data and predicts, for each given input, which of two possible classes forms the output. In our paper, we use six different classes of images.
X.C. He. and N.H.C. Yung. “Curvature scale space corner detector with adaptive threshold and dynamic region of support.” International conference on pattern recognition, Vol. 2, pp 791-794, 2004.
X.C. He. and N.H.C. Yung. “Corner detector based on global and local curvature properties.” Optical engineering, vol. 47, no. 5, pp. 057008(1-12), 2008.
O. Ludwig, D. Delgado, V. Goncalves and U. Nunes. “Trainable classifier-fusion schemes: an application to pedestrian detection.”Conference on intelligent transportation systems, vol. 1, pp 432-437, 2009.
Cordelia Schmid. Class Lecture, Topic: “Bag-of-features for category recognition.” Paris, Sep. 4, 2013.
K. Teknomo. “Numeric example of k-means clustering.” Internet: http://www.people.revoledu.com/kardi/tutorial/kMean/NumericalExample.htm, [Nov. 29, 2013].
N. Dalal and B. Triggs. “Histograms of oriented gradients for human detection.” IEEE computer sciety conf.erence on computer vision and pattern recognition, vol. 1, pp. 886-893, 2005.
O. Stephen and A.D. Bruce. “Introduction to the bag of features paradigm for image classification and retrieval.” Computing research repository, vol. arXiv:1101.3354v1, 2011.
Y. Lee, Y. Lin,and G. Wahba. "Multicategory support vector machines: theory and application to the classification of microarray data and satellite radiance data.” Journal of american statistical association, vol. 99 (4655), pp. 67-81, 2004.
B. Green “Canny Edge Detection Tutorial.” Internet: http://www.scribd.com/doc/40036113/Canny-Edge-Detection-Tutorial, 2002 [Nov. 01, 2015].
R. Wang. “Canny edge detection.” Intenet: http://fourier.eng.hmc.edu/e161/lectures/canny/node1.html, Sep. 25, 2002 [Nov. 01, 2015].
J. Fogarty, R.S. Baker and S.E. Hudson. “Case studies in the use of ROC curve analysis for sensor-based estimates in human computer interaction” Proceedings of graphics interface, pp. 129-136, 2005.
D. M. W. Powers. “Evaluation: From precision, recall and f-measure to ROC, informedness, markedness & correlation.” Journal of machine learning technologies, vol. 2(1), pp-37-63, 2011.
J. Schneider. “Cross Validation. Internet: http://www.cs.cmu.edu/~schneide/tut5/node42.html, Feb. 7, 1997 [Nov. 02, 2015].
R. Kohavi."A study of cross-validation and bootstrap for accuracy estimation and model selection." Proceedings of the fourteenth international joint conference on artificial intelligence, pp 1137–1143, 1995.
A. Bosch, A. Zisserman and X. Muñoz. “Image classification using random forests and ferns”. Proceedings of Asian conference on computer vision, Tokyo, Japan, 2007.
V. Andersen; L. Pellarin; R. Anderson, “Scale invariant feature transform (SIFT): performance and application”, The IT University of Copenhagen, pp, 1-14, 2006.
D. G. Lowe. “Distinctive image features from scale-invariant key points”, International journal of computer vision, vol. 60, pp. 91-110, 2004.
N. I. Cinbis; S. Sclaroff, “Object, scene and actions: Combining multiple features for human action recognition”, Proceeding of European conference on computer vision , 2010, pp 494-507.
A. Bosch; A. Zisserman; X. Muñoz, “Scene classification using a hybrid generative/discriminative approach”, IEEE Transaction on pattern analysis and machine intelligence, vol. 30 no. 4, pp. 712-727, 2008.
Authors who submit papers with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
- By submitting the processing fee, it is understood that the author has agreed to our terms and conditions which may change from time to time without any notice.
- It should be clear for authors that the Editor In Chief is responsible for the final decision about the submitted papers; have the right to accept\reject any paper. The Editor In Chief will choose any option from the following to review the submitted papers:A. send the paper to two reviewers, if the results were negative by one reviewer and positive by the other one; then the editor may send the paper for third reviewer or he take immediately the final decision by accepting\rejecting the paper. The Editor In Chief will ask the selected reviewers to present the results within 7 working days, if they were unable to complete the review within the agreed period then the editor have the right to resend the papers for new reviewers using the same procedure. If the Editor In Chief was not able to find suitable reviewers for certain papers then he have the right to reject the paper.
- Author will take the responsibility what so ever if any copyright infringement or any other violation of any law is done by publishing the research work by the author
- Before publishing, author must check whether this journal is accepted by his employer, or any authority he intends to submit his research work. we will not be responsible in this matter.
- If at any time, due to any legal reason, if the journal stops accepting manuscripts or could not publish already accepted manuscripts, we will have the right to cancel all or any one of the manuscripts without any compensation or returning back any kind of processing cost.
- The cost covered in the publication fees is only for online publication of a single manuscript.