Note: Descriptions are shown in the official language in which they were submitted.
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TITLE:
Bird Identification System
FIELD
The present invention relates to a user interface that is used with software
to assist
bird watchers in identifying birds that have been sighted.
BACKGROUND
U.S. Patents 6,546,368 and 6,772,142 are examples of existing approaches to
bird
identification with the assistance of software.
SUMMARY
According to the present invention there is provided a flora and fauna
identification
apparatus. There is a flora and fauna database that has a plurality of
records. Each record has
a color representation of a particular flora or fauna, along with a plurality
of fields of
identification criterion including physical topography and coloration of
selected regions of the
physical topography. There is provided a user interface, and a processor that
selects records
that are possible matches from the database based upon input of identification
criterion by a
user through the user interface. The user interface has a physical topography
selector from
which the user selects, from a plurality of possible physical topographies, a
selected physical
topography most closely resembling a flora or fauna to be identified. The
processor
determines the records in the database that are possible matches based upon
the selected
physical topography. There is also provided a pallet of colors, from which the
user
sequentially selects colors and places the colors on selected regions of the
selected physical
topography. The processor determines the records in the database that are
possible flora or
fauna matches as each color is added and placed on the selected region of the
physical
topography template.
BRIEF DESCRIPTION OF THE DRAWINGS
These and other features of the invention will become more apparent from the
following description in which reference is made to the appended drawings, the
drawings are
for the purpose of illustration only and are not intended to in any way limit
the scope of the
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invention to the particular embodiment or embodiments shown, wherein:
FIG. 1 is a schematic view of a flora and fauna identification system.
FIG. 2 is a flowchart of a method for identifying flora and fauna.
FIG. 3 through 8 are screenshots of a program used to identify flora and
fauna.
FIG. 9 is a schematic view of a topography template with physical features
being
added.
DETAILED DESCRIPTION
The preferred embodiment, a flora and fauna identification apparatus will now
be
described with reference to FIG. 1 through 9. While the description below is
given in relation
to bird identification, it will be understood that the same principles may be
applied to identify
other types of flora and fauna, such as flowers, butterflies, frogs or snakes.
Referring to FIG. 1, the bird identification apparatus includes a bird
database 12 that
has a plurality of records. Each record in database 12 has a color
representation of a
particular bird, along with a plurality of fields of identification criterion
such as physical
topography and coloration of selected regions of the physical topography.
Other criteria may
include geographical location based upon migratory patterns, distinctive
physical features,
texture, observed natural habitat, or relative size ranking. A user interface
20 allows a user to
access database 12, and a processor 22 selects records that are possible
matches from database
12 based upon input of identification criterion by a user through user
interface 20. While one
particular arrangement has been shown, there are a variety of ways providing
database 12,
user interface 20, and processor 22. For example, user interface 20 may be a
computer as
depicted. The user interface may also be a portable computer, such as a
laptop, PDA, cell
phone, etc. Database 12 may be an online database that the user interface 20
connects to,
such as a web page, or it may be loaded directly onto the user interface,
which may be
preferable if a portable computer is used, which will not have an internet
connection in the
field. If database 12 is an online database, the processor 22 in the remote
server 23 may be
used. Alternatively, if software is loaded onto the user interface 20, the
processor 22 of user
interface 20 may be used. Alternatively, certain functions may be divided
between user
interface 20 and database 12 to improve performance, or a combination of the
two, as will be
known to those in the art.
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Referring to FIG. 3, user interface 20 has various selectors which allow the
user to
narrow the possible type of bird that was observed. For example, a physical
topography
selector 24 may be provided, from which the user selects a physical topography
26 most
closely resembling the bird to be identified from a plurality of possible
physical topographies
displayed in selector 24. Once selected, physical topography 26 then appears
on a working
area 28. From this selection, processor 22 determines the records in database
12 that are
possible matches. The user then sequentially selects colors from a pallet 25
of colors and
places the colors on selected regions of physical topography 26. Referring to
FIG. 4, a
paintbrush 30 is used to represent a color selection tool. Processor 22
provides the color
representations taken from records in database 12 of the possible matches as
each color is
added and placed on the selected region of the physical topography template
26. Placing
paintbrush 30 over an area of topography template 26 that is more detailed may
cause that
area to be magnified on working area 28. Other identification criteria that
may be specified
include:
o Geographical location based upon migratory patteins. The user interface 20
allows
the user to input the geographical location and time of year of the sighting.
The
selected location is indicated in the location field 32, and the selected
season is
represented by the season field 34.
o Distinctive physical features. The user interface 20 enables the boundaries
of the
selected physical topography 26 of the bird to be modified by the user to
denote
distinctive physical features. An example of this is shown in FIG. 9, where a
plume
42 and a rear peak 44 are added to physical topography 26 in order to
distinguish the
type of bird to be identified. While FIG. 9 shows optional features that may
be
included specific to the physical topography 26, it may also be done by
allowing the
lines on topography 26 to be manipulated, or by allowing topography 26 to be
stretched or shrunk in a certain direction to a more likely shape. Other
options to
specify the particular morphology include menus to specify characteristics
such as bill
shape (including thick, thin, short, long, hooked, etc.), tail shape (notched,
forked,
rounded, pointed, upright, square, fan, etc.), tail/neck/leg length, including
actual or
relative sizes (very short, short, average, long, very long), head crest,
outer tail feather
(corner, side, tip, banding, etc.), inner tail feather (comer, side, edge), or
wing tip
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colour. If desired, some menus or options may be available for certain
topographies
and not others. Furthennore, selecting certain features may adjust topography
26 on
display area 28.
o Texture. Referring to FIG. 3, the user interface 20 allows the user to
select a selected
texture from a plurality of possible textures shown in a texture toolbar 35.
o Relative size ranking. Referring to FIG. 3, the user interface 20 allows the
user to
select a size by either providing a measurement scale 36 that the user may use
to
indicate the approximate size of the bird to be identified, or by providing
relative size
rankings from which a selected relative size ranking may be selected.
o Observed natural habitat. The user interface 20 may also allow the user to
select a
selected habitat from a plurality of possible natural habitats (not shown).
One option
is to displaying picture showing various habitats, or a menu may also be
provided,
with a list including habitats such as: field, forest, lake, marsh, alpine,
desert, ocean,
shore, etc. Another option would be to provide a toolkit of natural object to
drag onto
the display area 28.
o Behaviour. Another menu (not shown) may specify the particular behaviour of
the
bird, such as swimming, dabbling, diving, plucks, wades, forages, walks,
perches, tree
cling, bobbing tail, flitting, etc.
o Movement patterns. The user may also be able to specify a bird's flight
pattern, again
by using a menu including options such as soaring, flocking, tight formation,
loose
formation, "V" formation, steady, bobbing, fly catching, level, etc. The user
may also
specify movement on land: hopping, walking, etc. The user may also specify
movement in relation to water: swimming, dabbling, diving, etc.
As more information is entered, records that are possible matches are ranked,
and a
list 40 of possible matches is displayed on the user interface. A score may be
assigned based
on how closely each match corresponds to the criteria the user has entered. In
this way, the
user may be able to identify the matching bird without having to specify all
the possible
criteria. In addition, the order in which the identification criteria are
specified may proceed in
any practical order, such that the observed natural habitat, geographic
location and time of
year may be specified to narrow the list of possible records before proceeding
to specify the
physical characteristics of the bird itself. It is important to note that the
user is not limited to
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a single selection in each category. There may be situations in which more
than one selection
may be made in each category. For example, some birds like to be on the edge
of field and
forest and will be observed in each. For example, some water fowl will both
swim and
dabble, but will not dive; other water fowl will swim and dive, but will not
dabble.
5
The ranking may be done in different ways. For example, an algorithm may
generate
a matching score for each record by comparing each criteria entered by the
user with the
criteria stored in the database. Each record is given a score based on whether
the criteria is a
perfect match, a near perfect match, does not match, or unspecified. For
example, if black
was entered, this may be scored as near perfect for a record that is dark
brown, and wrong for
a record that is light green. As another example, a color specified for the
throat will also be
compared to the color of the neck in the records, but not the tail. Thus, the
algorithm takes
into account that the user may be mistaken on some details. As a result, an
error in user input
when making selection from the various identification criterion will affect
the ranking of a
particular record, but does not eliminate the record as a possible match. For
example, an error
in the selected region in which a color is placed will affect the ranking of a
record, but it will
not be eliminated as a possible match. As more information is entered,
processor 22 updates
the rankings and generates a new list of possible matches. The algorithm may
also
incorporate a machine learning algorithm, where previous successful matches
made by users
are used as a training set. This may be useful when dealing with colors,
since, depending on
the pallet of colors used, the number of shades available may be limited, and
some users may
choose a different shade that does not correspond with the database record.
Referring to FIG. 2, an example of a flowchart to implement software with
three
selection criteria is shown. The process begins at step 50. From this step,
the user will either
select a topography in step 52, select a color for the topography in step 53,
or select a location
in step 54. If a location is selected, the location is compared against the
range database in step
56, possible matches and their probabilities are determined based on location
in step 58, and
displayed in step 60. Note that the location may be automatically entered
based on the user's
preferences or location, in which case the process would proceed automatically
from start at
step 50 to displaying possible matches and their probabilities in step 60. If
a color or
topography is selected in steps 53 or 52, respectively, the process proceeds
to compare the
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entered information even when incomplete in step 62 to the characteristics
diagram in step 64.
Probable matches are then determined in step 66 based on the diagram, and the
possible
matches and their probabilities are displayed in step 60. The user then either
proceeds to step
68 and selects the best match, or returns to the top to change or add more
detail in steps 52, 53
or 54. Once the best match has been selected in step 68, information is then
displayed about
the match. If not successful, the user may again return to the top to correct
or add more
information.
Referring to FIG. 3 through 5, an example of a program implementing the
procedure
described above is shown. Referring to FIG. 3, physical topography 26 is
selected from a set
of topographies displayed in topography selector 24, which then appears in
working area 28.
At the same time, a set of best matches appears in list 40. Paintbrush tool 30
is used to select a
color from pallet 25. Referring to FIG. 4, as paintbrush tool 30 moves toward
the head, the
head is magnified such that the user is able to color the desired area more
easily. List 40 is
updated to account for the color that has been specified. Referring to FIG. 5,
list 40 is
updated again as the user indicates another color on topography template 26.
Referring to
FIG. 6, the user has reset the application, and has selected a different
topography template 26.
Steps similar to those described above are taken through FIG. 7 and 8, with
list 40 being
updated after each step is taken.
In this patent document, the word "comprising" is used in its non-limiting
sense to
mean that items following the word are included, but items not specifically
mentioned are not
excluded. A reference to an element by the indefinite article "a" does not
exclude the
possibility that more than one of the element is present, unless the context
clearly requires that
there be one and only one of the elements.
It will be apparent to one skilled in the art that modifications may be made
to the
illustrated embodiments without departing from scope of the Claims.
