Title :
An approach of categorize natural scene images based on visual characters and LDA model
Author :
Bin-wei, Yang ; Yun, Zhang
Author_Institution :
Coll. of Comput. Eng., Zhejiang Inst. of Mech. & Electr. Eng., Hangzhou, China
Abstract :
In this paper, we will propose a new approach about how to categorize viewfinder images captured by digital cameras. This new unsupervised learning approach based-on visual characters of the images and LDA (Latent Dirichlet Allocation) model. In this approach, we represent the image of a scene by a collection of local regions, denoted as codewords. The image codewords which include visual characters of images are training units prepared for image categorizing. After learning, we get the LDA model parameters for each category image, and then in categorizing, we classify the input image by selecting the best category model. The test result shows that this approach can categorize different scenes automatically and works well.
Keywords :
image representation; image sensors; unsupervised learning; LDA model; categorize natural scene images; digital cameras; image codewords; image representation; latent dirichlet allocation; unsupervised learning approach; visual characters; Accuracy; Fires; Histograms; Image color analysis; Snow; Vectors; Visualization; LDA model; image categorize; visual character;
Conference_Titel :
Computer Science & Education (ICCSE), 2012 7th International Conference on
Conference_Location :
Melbourne, VIC
Print_ISBN :
978-1-4673-0241-8
DOI :
10.1109/ICCSE.2012.6295189