An Algorithm of Small Object Detection Region Proposal Search Based on GN Splitting

Peiran Zhao; Xinyuan Wu; Xinyu Tang; Xiaohai Shen; Haiyan Xu; Min Li; Xuewu Zhang

doi:10.3788/AOS201838.0915005

Acta Optica Sinica, Volume. 38, Issue 9, 0915005(2018)

An Algorithm of Small Object Detection Region Proposal Search Based on GN Splitting

Peiran Zhao^*, Xinyuan Wu, Xinyu Tang, Xiaohai Shen, Haiyan Xu, Min Li, and Xuewu Zhang^*

Author Affiliations

College of Internet of Things Engineering, Hohai University, Changzhou, Jiangsu 213022, China

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Abstract Get PDF(in Chinese)

Figures & Tables(7)

Fig. 1. Schematic of connected graph

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Fig. 2. Segment by Quick Shift algorithm. (a) Original image; (b)segmented result

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Fig. 3. Part of experimental results with Sk=3.5, dmax=13.5. (a) Airplane; (b) sheep; (c) car; (d) buoy

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Fig. 4. Relationship between time consumption and number of segment regions

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Table 1. Algorithm flow

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Table 1. Algorithm flow

Algorithm 1: GN_RP
Input: (color) image
Output: Set of small object location boxes B
Obtain initial regions R={r_i}using Quick Shift
Calculate histograms from different color space in r_i
Foreach Neighbouring region pair (r_i.r_j) do
Calculate similarity S(i,j) as the weight w_ij
Generate graph G by neighbor node pair and similarity
Sort w_ij in an ascending order
While w_ij<w_thr do
Delete e_ij from G
Extract set of connected subgraph G'from G_cut
Delete the maximum connected subgraph in G'
Extract object location boxes B from G'

Table 2. Effects of segmentation parameters on the results
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Table 2. Effects of segmentation parameters on the results
Types of different parameters Recall/% Number of proposals
S_k=5.0, d_max=20.0 70.04 12.06
S_k=3.5, d_max=20.0 71.60 22.17
S_k=5.0, d_max=13.5 81.26 23.38
S_k=3.5, d_max=13.5 84.09 41.14
S_k=2.5, d_max=13.5 78.44 50.49

Table 3. Comparison of results using different algorithms

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Table 3. Comparison of results using different algorithms

Types of different search	Recall/%	Time/s	Number of proposals
Exhaustion search (9900)	80.55	0.004	9900
SS(S_scale=80, S_min=50)	61.84	0.113	111.86
SS(S_scale=30, S_min=10)	82.89	0.565	700.82
GN_RP(S_k=3.5, d_max=13.5)	84.09	0.068	41.14

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Peiran Zhao, Xinyuan Wu, Xinyu Tang, Xiaohai Shen, Haiyan Xu, Min Li, Xuewu Zhang. An Algorithm of Small Object Detection Region Proposal Search Based on GN Splitting[J]. Acta Optica Sinica, 2018, 38(9): 0915005

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