An interactive flower image recognition system

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62 Multimed Tools Appl (2011) 53:53–73Fig. 9 The HS color spaceis divided into 12×6 color cellsappearing in the flower region. The color coordinates of these three dominant color cellsand their corresponding probabilities are taken as the color features of the flower region.Let (dx i , dy i ) and p i denote the coordinate vector and the corresponding probability of DC(i), 1 ≤ i ≤ 3, where dx i = S DC(i) cos(H DC(i) ) and dy i = S DC(i) sin(H DC(i) ). These color featurescan be summarized as follows.CF 1 : x-coordinate value of DC 1 , dx 1CF 2 : y-coordinate value of DC 1 , dy 1CF 3 : the probability of DC 1 , p 1CF 4 : x-coordinate value of DC 2 , dx 2CF 5 : y-coordinate value of DC 2 , dy 2CF 6 : the probability of DC 2 , p 2CF 7 : x-coordinate value of DC 3 , dx 3CF 8 : y-coordinate value of DC 3 , dy 3CF 9 : the probability of DC 3 , p 3Shape features of flower region To get the shape features, we first define the centroid (g x ,g y ) of the flower region as the flower center, which is computed as follows:g x ¼ 1 NX Ni¼1x i ;ð6Þg y ¼ 1 Nwhere N is the number of pixels on the flower boundary, x i and y i are respectively the x andy coordinates of the i-th boundary pixel. The distance between the flower center and eachboundary pixel is then computed as follows:qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffid i ¼ ð Þ 2 2þ y i g y ; 1 i N: ð8Þx ig xX Ni¼1y i ;ð7Þ
Multimed Tools Appl (2011) 53:53–73 63Without loss of generality, let the distances be sorted in an increasing order. That is, d i ≤d i+1 , for 1 ≤ i ≤ N-1. The three shape features (notated SF 1 , SF 2 , and SF 3 ) used to representthe shape characteristics of the flower region will be described as follows.1) SF 1 : A ratio which indicates the relevant sharpness of the petals and is computed fromthe distances between the flower boundary points to the flower center defined as follows:SF 1 ¼ R 10;ð9ÞR 90where R 10 and R 90 are respectively the average distances among all d i ’s which aresmaller than 10th percentile and larger than 90th percentile of all d i ’s:R 10 ¼10:1 N0:1N Xi¼1d i ;ð10ÞR 90 ¼10:1 N0:1N Xi¼1d N i : ð11ÞNote that the computed feature value SF 1 defined as a ratio between R 10 and R 90 will notchange greatly when the flower region is broken or captured from different directions.2) SF 2 : The average of normalized distances computed from every flower boundary pointto the flower center defined as follows:SF 2 ¼ 1 D i ;ð12ÞNi¼1where D i is the normalized distance defined as follows:8< 1; d i R 90dD i ¼ i R 10R 90 R 10; R 10 < d i < R 90 : ð13Þ:0; d i R 10Note that the definition of the feature value SF 2 using the averaged normalized valuesD i ’s will make it invariant to the size of the flower region.3) SF 3 : Roundness measure which indicates how much the shape of the flower petal iscloser to a circle and is defined as follows:X NSF 3 ¼ 4pSL 2 ; ð14Þwhere L is the length of the flower boundary and S is the area of the flower regiondefined as the total number of pixels in the flower region. When the flower shape isclose to a circle, SF 3 will be close to 1. Note that this feature value is robust to rotation,translation, and scaling of flower objects.In summary, the 12-dimensional feature vector used to represent the flower region can bedescribed as follows:f F ¼ ½CF 1 ; CF 2 ; ; CF 9 ; SF 1 ; SF 2 ; SF 3 Š T : ð15Þ
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An interactive flower image recognition system

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