Image retrieval evaluation on smart phone using variant of histogram of gradient

Lalit B. Damahe, Nileshsingh V. Thakur, Sachin R. Jain, Shailesh D. Kamble
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Abstract

The retrieval of similar type of data is performed by requesting the query, generally through personal computer. As the smart mobile devices are available at the general user, retrieval of visually similar data is now performed on these devices such as smart phones, PDA etc. A wireless medium is the key component of mobile devices and visually similar image retrieval with minimum latency is the typical issue.Hence the main objective of our proposed work is to develop the efficient mechanism for image retrieval on mobile devices. The image representation scheme V-HOG captures the useful information from the image with the help of gradient vector and the gradients are calculated by using various block size. The size of block, cell and bins are the main components which are varied and developed the V-HOG with feature values 1296, 1176, 672. The experimentation are conceded on the standard Holidays Dataset. The proposed V-HOG approach having a feature value 1296, 1176 and 672 perform better with existing HOG. In comparison with HOG, the precision and recall rate for V-HOG is improved by 27% to 90% and 7% to 32% respectively. The retrieval time is also reduced to 3% to 9%. The proposed V-HOG with 1176 feature perform well and having a good precision and recall rate.
基于梯度直方图变体的智能手机图像检索评价
类似类型数据的检索是通过请求查询来执行的,通常是通过个人计算机。由于一般用户都可以使用智能移动设备,检索视觉上相似的数据现在是在这些设备上进行的,例如智能手机、PDA等。无线媒体是移动设备的关键组件,具有最小延迟的视觉相似图像检索是典型问题。因此,我们提出的工作的主要目标是开发在移动设备上有效的图像检索机制。图像表示方案V-HOG利用梯度向量从图像中获取有用信息,并利用不同的块大小计算梯度。块、单元和箱的大小是变化的主要组成部分,形成了特征值为1296、1176、672的V-HOG。实验是在标准假日数据集上进行的。本文提出的特征值为1296、1176和672的V-HOG方法与现有的HOG方法相比性能更好。与HOG相比,V-HOG的查准率和查全率分别提高了27% ~ 90%和7% ~ 32%。检索时间也减少到3% ~ 9%。所提出的具有1176特征的V-HOG性能良好,具有良好的查准率和查全率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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