Classifying – separating – and assorting solids – Sorting special items – and certain methods and apparatus for... – Condition responsive means controls separating means
Reexamination Certificate
1999-12-14
2002-06-25
Walsh, Donald P. (Department: 3653)
Classifying, separating, and assorting solids
Sorting special items, and certain methods and apparatus for...
Condition responsive means controls separating means
C209S576000, C209S580000, C209S587000, C209S938000
Reexamination Certificate
active
06410872
ABSTRACT:
TECHNICAL FIELD
This invention relates to agricultural product inspection and more particularly to an apparatus and a method of inspecting peach halves for pits and pit fragments.
BACKGROUND OF THE INVENTION
A popular agricultural product is canned peach halves, slices and cubes. The peach variety typically used for canning is referred to as a “cling” peach, whereas the popular eating peach variety is referred to as “the free stone” peach, which is not used for canning because they lose their taste during the canning process. The variety names cling and free stone imply the relative ease with which the stone (hereafter “pit”) can be removed from the fruit.
Many peach processors employ an Atlas splitting machine to remove the pit. This machine consist of a circumferential knife, that looks and functions much like the iris of a camera lens. As the blades of the machine close down on the peach, it cuts through the flesh until it meets the hard core of the pit. Once the pit is secured firmly in place by means of the blade, two cups approach from either side to grab the two peach halves. When the cups are in place they are rotated in opposite directions to twist the peach halves apart and separate them from the secured pit. Unfortunately, the blade cannot always adequately secure the pit and when the peach halves fall away, the entire pit may stay embedded in one of the halves. Alternatively, the pit may split in half or fragment into smaller pieces.
Successful removal of pits from cling peaches presents a considerable agricultural processing challenge. In conventional agricultural processing plants, split peach halves are visually inspected for pits or pit fragments by large numbers of inspectors standing on opposite sides of conveyors belts used to transport the peach halves. Unfortunately, the pit color closely matches the color of peach flesh. This is due in part to tendrils of peach flesh that cling to the surface of the pit. Therefore, the inspectors must rely on their visual shape recognition capabilities to recognize unacceptable product. Moreover, the inspectors often have to manually detect small “hidden” pit fragments by wiping the tip of their fingers around the cavity left in the peach by a removed pit. These inspection difficulties have previously ruled out automatically inspecting peach halves with machine vision techniques that detect visual wavelengths of light because the close color match between peach flesh and pits and the hidden nature of many pit fragments would render such inspection unreliable.
Improving machine vision inspection reliability involves careful attention to the camera or cameras employed, the illumination of the product being inspected, and the image processing methodologies. Suitable illumination typically employs a uniform, shadowless, high intensity light source to illuminate the product being inspected. Prior light sources include fluorescent lamps, incandescent bulbs, and short and long arc discharge lamps. The assignee of this application, SRC Vision, of Medford, Oreg. has used all of these sources and found them wanting in one aspect or another.
For example,
FIG. 1
shows a “Brite-Lite” illumination source
10
manufactured by the assignee of this application, in which a fluorescent tube
12
is mounted at one foci of an elliptical or parabolic reflector
14
and the other foci lies in a linear inspection zone
16
on the plane of a conveyor belt
18
moving articles
20
to be inspected. A line scanning inspection camera
22
has its field of view that is co-aligned with the energy from fluorescent tube
12
focused in inspection zone
16
to maximize the amount of illumination reflected off articles
20
and received by inspection camera
22
. This illumination technique produces a fairly uniform illumination inspection zone
16
, but the illumination decreases near the edges of belt
18
because light illuminating the center of belt
18
propagates from any and all points along the length of fluorescent tube
12
. However, because fluorescent tube
12
has a finite length and extends only five or six inches beyond the belt edges, illumination reaching points near the belt edges propagates mainly from portions of fluorescent tube
12
directly over the belt and, to a lesser extent, from any short portions that extend beyond the belt edges. Moreover, this technique is not entirely shadowless, which makes pit fragment detection difficult. Consider an article with some height, such as an apple cube lying within inspection zone
16
. A point lying immediately to one side of the cube will receive light from only that portion of fluorescent tube
12
that extends in a direction away from that side of the cube. The cube itself will block the light from that portion of fluorescent tube
12
that extends in the direction of the cube. There is, however, some partial filling in of the shadow by that portion of fluorescent tube
12
that is not blocked by the cube.
To provide shadowless illumination, the light rays should ideally be parallel and perpendicular to the surface of belt
18
. One way to produce this ideal illumination is to employ an illumination point source at an infinite distance. However, this technique is impractical because the illumination intensity decreases inversely with the square of the distance from the light source.
FIG. 2
shows another exemplary illumination source
30
that employs multiple incandescent lamps
32
each having an associated reflector. Illumination source
30
simulates multiple illumination point sources propagating from a significant distance, but is not very energy efficient because the illumination from each of lamps
32
is spread over a relatively large area of belt
18
. Illumination uniformity is approximated by appropriately aiming lamps
32
and by adjusting their individual illumination levels. This is a labor intensive process that is prone to errors. Moreover, indiscriminate adjustment of lamp
32
illumination levels may alter their spectral wavelength distributions.
FIG. 3
shows yet another exemplary illumination source
40
that employs a pair of moderate length high-intensity discharge (“HID”) tubes
42
positioned at the foci of two astigmatic cylindrical projection lenses
44
. In illumination source
40
, only those light rays that intersect flat back surfaces
46
of projection lenses
44
are focused on inspection zone
16
of conveyor belt
18
, which renders this technique inefficient. Moreover, because the lengths of HID tubes
44
is short compared to the width of belt
18
, the light rays must diverge to spread across the width of belt
18
, which introduces shadows because the angle of incidence of the light rays is not perpendicular to belt
18
. Using multiple HID lamps
44
and projection lenses
44
can somewhat alleviate this problem.
What is needed, therefore, is an illumination and detection technique and image processing methodology that is suitable for automatically inspecting peach halves, slices, and dices for pits and pit fragments.
OBJECTS OF THE INVENTION
An object of this invention is, therefore to overcome the shortcomings of the prior art.
Another object of this invention is to provide an automated electro-optical means for detecting faulty articles in a low contrast and low signal level environment.
A further object of this invention is to provide for the automated detection of peach pits and pit fragments in peach flesh.
Yet another object of this invention is to provide an illumination source, a detector, and an image analysis method suitable for achieving the objects of this invention.
In the context of this invention, contrast C is defined as follows:
C
=
R
λ
PIT
R
λ
FLESH
or
S
PIT
S
FLESH
where R≡Reflectivity and S≡Signal (Intensity). S is further defined as:
S
=
∫
λ
1
λ
2
R
(
λ
)
L
(
λ
)
C
(
λ
)
F
(
λ
)
ⅆ
λ
where R(&lgr;)≡the spectral reflectivity of an article; L(&l
Campbell Duncan B.
Ewan James
Kalayeh Hooshmand M.
Leidecker Cliff J.
Squyres H. Parks
Key Technology Inc.
Rodriguez Joseph
Walsh Donald P.
Wells St. John P.S.
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