Speckle extraction and adjacent point vector method-based fruit image matching method
A matching method, vector method technology, applied in fruit image matching based on spot extraction and adjacent point vector method, in the field of fruit image matching, it can solve problems such as high method requirements, elimination of wrongly matched points in fruit images, and noise in the data set
Active Publication Date: 2014-09-10
杭州诺田智能科技有限公司
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[0005] However, the online detection and grading of fruits has high requirements on the method. On the one hand, the SIFT method has caused the complexity of the method to improve the matching adaptability, so the calculation amount is large and time-consuming, and the original SIFT method cannot meet the online requirements; on the other hand , the commonly used false matching point elimination method RANSAC method (Chum O, Matas J.Optimal randomized RANSAC[J].IEEE Trans.On Pattern Analysis and Machine Intelligence,2008,30(8):1472-1482) The basic assumption is that in the sample Contains correct data (inliers, data that can be described by the model), as well as abnormal data (Outliers, data that deviates far from the normal range and cannot adapt to the mathematical model), that is, the data set contains noise
These abnormal data may be caused by wrong measurements, wrong assumptions, wrong calculations, etc., and the small difference in fruit coding color features makes it impossible to obtain matching points stably for fruit image matching based on the SIFT method. The number of matching points obtained by one match is 0 to more, so this method cannot be used to eliminate mismatching points of fruit images
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[0072] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0073] Such as figure 1 Shown, the inventive method comprises the steps:
[0074] 1) Get the side image of the fruit:
[0075] Place the fruit on the fruit tray so that the calyx and fruit stem of the fruit are basically perpendicular to the horizontal plane, collect a left side image from the side of the fruit, and then use the fruit calyx and fruit stem as the axis, rotate the fruit 60° and then Acquire a right profile image.
[0076] 2) Perform spot extraction. Spot extraction includes the following three methods to obtain the left and right spot sets:
[0077] 2.1) Extreme point detection:
[0078] First, the left side image and the right side image are calculated according to the following formula 1 to obtain the initial Gaussian left image and the initial Gaussian right image:
[0079] L(x,y,σ)=G(x,y,σ)*I(x,y) (1)
[0080] Among them, L(x,y,...
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The invention discloses a speckle extraction and adjacent point vector method-based fruit image matching method. The method includes the following steps that: a left side surface image and a right side surface image of fruit are obtained; speckle extraction is performed, and a left image speckle set and a right image speckle set are obtained through respectively adopting an extreme point detection method, a Harris angular point detection method and a Canny edge detection method; matching judgment is performed on each point in the sets to obtain a matching point to be selected set; fault matching deletion is performed on the matching point to be selected set so as to perform screening to obtain a right matching point set; and fruit image matching is completed. According to the extraction and adjacent point vector method-based fruit image matching method of the invention, speckle extraction is performed, and vector method judgment is performed on speckles, and therefore, excellent stability, accuracy and timeliness of fruit image matching can be realized.
Description
technical field [0001] The invention relates to a fruit image matching method, in particular to a fruit image matching method based on spot extraction and adjacent point vector method in the technical field of image processing. Background technique [0002] Image matching refers to identifying the same point between two or more images through a certain matching method. In recent years, image matching has become a key technology and research hotspot in the fields of image analysis and processing such as object recognition, robot map perception and navigation, image stitching, 3D model building, gesture recognition, image tracking, and motion comparison. [0003] The acquisition of fruit surface information is the basis for the detection of fruit quality indicators such as size, shape, surface color and surface defects. The accuracy of surface color and surface defect detection depends on the acquisition of complete fruit surface images. Image mosaic technology is the key to ...
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IPC IPC(8): G06T7/00
Inventor 饶秀勤林文彬应义斌
Owner 杭州诺田智能科技有限公司