  In this paper, we developed the system for recognizing the orchid species by
using the images of flower. We used MSRM (Maximal Similarity based on Region
Merging) method for segmenting the flower object from the background and
extracting the shape feature such as the distance from the edge to the centroid
point of the flower, aspect ratio, roundness, moment invariant, fractal
dimension and also extract color feature. We used HSV color feature with
ignoring the V value. To retrieve the image, we used Support Vector Machine
(SVM) method. Orchid is a unique flower. It has a part of flower called lip
(labellum) that distinguishes it from other flowers even from other types of
orchids. Thus, in this paper, we proposed to do feature extraction not only on
flower region but also on lip (labellum) region. The result shows that our
proposed method can increase the accuracy value of content based flower image
retrieval for orchid species up to $\pm$ 14%. The most dominant feature is
Centroid Contour Distance, Moment Invariant and HSV Color. The system accuracy
is 85,33% in validation phase and 79,33% in testing phase.
