An Improved Image Classification Method Based On Spatial Pyramid Matching Framework
نویسندگان
چکیده
منابع مشابه
Improved Spatial Pyramid Matching for Image Classification
Spatial analysis of salient feature points has been shown to be promising in image analysis and classification. In the past, spatial pyramid matching makes use of both of salient feature points and spatial multiresolution blocks to match between images. However, it is shown that different images or blocks can still have similar features using spatial pyramid matching. The analysis and matching ...
متن کاملImproved Arabic Word Classification using Spatial Pyramid Matching Method
In recent years, rapidly developed hand written word recognition techniques have attracted researcher’s attention to study Arabic word classification. Arabic language has cursive style of writing so it needs special framework for classification. In this paper, a precise framework for Arabic word classification is presented, which uses sparse coding with spatial pyramid matching (SPM) algorithm ...
متن کاملImage Classification Using Sparse Coding and Spatial Pyramid Matching
Recently, the Support Vector Machine (SVM) using Spatial Pyramid Matching (SPM) kernel has achieved remarkable successful in image classification. The classification accuracy can be improved further when combining the sparse coding with SPM. However, the existing methods give the same weight of patches of SPM at different levels. Clearly the discriminative powers of SPM at different levels are ...
متن کاملFast Low-rank Representation based Spatial Pyramid Matching for Image Classification
Recently, Spatial Pyramid Matching (SPM) with nonlinear coding strategies, e.g., sparse code based SPM (ScSPM) and locality-constrained linear coding (LLC), have achieved a lot of success in image classification. Although these methods achieve a higher recognition rate and take less time for classification than the traditional SPM, they consume more time to encode each local descriptor extracte...
متن کاملSpatial Pyramid Matching
This chapter deals with the problem of whole-image categorization. We may want to classify a photograph based on a high-level semantic attribute (e.g., indoor or outdoor), scene type (forest, street, office, etc.), or object category (car, face, etc.). Our philosophy is that such global image tasks can be approached in a holistic fashion: It should be possible to develop image representations t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: DEStech Transactions on Engineering and Technology Research
سال: 2016
ISSN: 2475-885X
DOI: 10.12783/dtetr/ssme-ist2016/4019