Wire bonding is a solid phase welding process, where the two metallic materials (wire and pad surface) are brought into
intimate contact. In order to ensure the accuracy and speed of bonding, micro-scoped pattern recognition systems (PRS)
are often used to measure the deviation of the actual chip relative to the sampling position (eye-point). In this paper, a
new mixed moment feature based matching algorithm is proposed for wire bonding. The important components of
Zernike moments and wavelet moments are extracted to compose the mixed moment vector. The realization of location
is by calculating the Euclidean distance of mixed moment vectors between the eye-point images and images to be
matched. Experimental results show the rotation, translation invariance of the mixed moment features. The algorithm can
improve the positioning accuracy while no increase in computational complexity, and can be well used in the precise
positioning of the vision system for wire bonding.
In order to measure the activities of <i>Nostoc flagelliforme</i> cells, a new method based on color identification was proposed
in this paper. <i>N. flagelliforme </i>cells were colored with fluoreseein diaeetate. Then, an image of colored N. flagelliforme
cells was taken, and changed from RGB model to HIS model. Its histogram of hue H was calculated, which was used as
the input of a designed BP network. The output of the BP network was the description of measured activity of <i>N.
flagelliforme</i> cells. After training, the activity of <i>N. flagelliforme </i>cells was identified by the BP network according to the histogram of H of their colored image. Experiments were conducted with satisfied results to show the feasibility and
usefulness of activity measurement of <i>N. flagelliforme </i>cells based on color identification.