A Study of Image Recognition on Kansei Engineering

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S y m b i o s i s o f H u m a n a n d A r t i f a c t

Y . A n z a i , K . O g a w a a n d H . M o r i ( E d i t o r s )

© 1995 E l sev i e r Sc i ence B .V. Al l r i gh t s r e se rved .

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A S t u d y o f I m a g e R e c o g n i t i o n o n K a n s e i E n g i n e e r i n ga b b

T . J in do , M. N ag ama ch i , an d Y . M at su b araa

V eh ic l e R esea rch L ab o ra to ry , N i s san R esea rch C en te r , N i s san M o to r C o . , L td .,

1 , N a t su sh im a-ch o , Y o k o su k a , Jap an

bH i ro sh ima U n iv e r s i ty , 4 -1, K ag am iy ama 1 -ch o me, H ig ash i H i ro sh ima , Jap an

K an se i en g in ee r in g i s a d i sc ip l in e th a t co n cern s th e c rea t io n o f p ro d u c t s t h a t co n v ey a

ce r t a in d es i r ed imag e to cu s to mers , b ased o n r esea rch in to th e r e l a t io n sh ip s b e tw een th eperceived imp ress ion o f a p roduct and it s physical p roper ties such as co lo r o r shape. Th is paper

presen ts the resu l ts o f a s tudy concern ing the c lass i f ica t ion o f the featu res o f p roducts which

tend to incorporate s p~ i a l iz ed o r sub ject ive e lements. An a t tempt was ma de in th is s tudy to use

ima g e r ec o g n i t io n t ech n o lo g y to ju d g e an d c l a s s i fy th e p h y s ica l p ro p er t i e s , i .e . , d es ig n

elements , o f the au tomot ive s teer ing wheel au tomat ical ly in o rder to e l iminate any sub ject ive

aspects .

1 . I N T R O D U C T I O N

T h e o v era l l f r am ew o rk o f t h is r e sea rch w as d e f in ed as th e f i r st s t ep to w ard th edevelopm ent o f a sys tem fo r au tomat ically c lass ify ing the des ign featu res o f au tomot ive s teer ing

whee ls . As a resu l t , the s ign i f icance o f au tomat ic featu re c lass i f ica t ion and the speci f ic deta i l s

o f the sys tem fo r execu t ing th is task were speci fied as exp la ined below.

The a im set fo r the au tomat ic featu re c lass i f ica t ion sys tem w as no t to descr ibe the physical

featu res o f an inpu t sam ple . Rather , i t was des i red that the sys tem sho u ld be ab le to c lass i fy the

featu res au tom at ical ly in to respect ive categor ies on the bas is o f p redetermined des ign e lements .

T ab le .1 s h o w s th e d es ig n e l emen t s an d ca t eg o r ie s th a t w ere d e f ined fo r au to m o t iv e s t ee r in g

wheels in th is s tudy .

In v iew of the fact that th is s tudy was being done a t the research level , i t was d ecided to

use a scanner to inpu t two-d imensional images such as i l lus t ra t ions and pho tographs in to thereco g n i t io n sy s t em. O n th e b asi s o f t h ese tw o -d imen s io n a l imag es , th e sy s t em w o u ld th en

automatically classify the steering wheel design features.

2 . D E L O P M E N T O F D E S IG N F E A T U R E R E C O G N I T I O N S Y S T E M U S I N G

S T E E R I N G W H E E L I L L U S T R A T I O N S

Template match ing i s f requen t ly used as a techn ique fo r recogn izing des ign featu res f rom

il lus t ra tions o f p roducts . Th is method w orks i f the des ign in quest ion i s amo ng several des ign

p a t t e rn s k n o w n in ad v an ce an d d o es n o t i n c lu d e an y d i sp lacemen t o r ch an g es . W i th th i s

method , an inpu t image is compared wi th templates , which have been p repared in advance ands to red in mem o ry , f ro m ev ery p o ss ib l e po s i ti o n . A n in d ex o f s im i l a r i ty b e tw een th e in p u t

ima ge and the templates i s found in every posit ion . At the po in t where the index reach es i t s



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m ax im um va lue , a j udg m en t i s made t ha t t he r e i s a temp la t e wh ich m a tches t he i npu t image a t

t ha t pos i ti on . Th i s m e thod can a l so j udge a de s ign pa tt e rn fo r wh ich t he i ndex o f s imi l a r i t y

s h o w s a m a x i m u m v a l u e a m o n g s e v e r a l t e m p l at e s. H o w e v e r , o n e d i s a d v a n t a g e o f t e m p l a t e

m a t c h i n g i s i ts e x t r e m e l y h i g h c o m p u t a t i o n a l c o s t s. A n o t h e r d r a w b a c k i s th a t p a t t e rn

recogn i t ion i s imposs ib le i f the input image inc ludes d i sp lacem ent or modi f ica t ions .

T a b l e . l . D e s i g n e l e m e n t s / c a te g o r i e s a n d r e l a t e d d e f i n i t i o n s

E l e m e n t C a t e g o r yNo . o f spokes 2

S p o k e a n g l e S m a l l

O p e n s p a c e e m p h a s iso r spoke emphas i s

S p o k e s a n d p a dcon t i nu i t yP re sence o f con tro lswi t ches

Horn pos i t ion

P r e s e n c e o f f m g e r

res t sSize of s ideopen space

P a d h e i g h t

P a d w i d th

Pad su r f ace pa t t e rn

iq,T0 B,!lf~

Shape o f padu p p e r e d g e

LargeOpen space emphas i sSpoke emphas i sP re sen tADsentNoneE m b e d d e d i n p a dOn s ide s

Pad t ypeEmbedded i n spokesPresentA b s e n tLa rgeS m a l l

N o n eL a r g eM e d i u mb m m lLargeM e d i u m

Def in i t ionA s t ee r ing wh ee l w i th two spok esA s t ee r ing whee l w i th t h r ee spokesA s tee r ing w hee l w i th fou r spokesSpace be tween spokes i s sma l lSpace be tween spokes i s l a rgeA type tha t accents the shape s o f the ooen spacesA type tha t accents the spoke shapesPad su r f ace and spokes a r e con t i nuousPact sur tace and spokes a re c t t scontmuousNo sw i tches on t he whee lSwi tches a re loca ted on the p adSwi t ches a r e loca t ed on t he s i de s o f t he whee lHorn bu t ton i s in tegra ted wi th the padHorn but ton i s loca ted on the spokesA typ e wi th f inger res t sA type w i thout f inger res t sSize of s ide open space i s l a rgeSize of side open spa ce i s smal l

There i s no s ic ie open spacePad i s la rge in he ightPad is med ium in he igh t?act sm all in nel~latPad i s l a rge in wid thPad i s med ium in w id th

Smal l Pad i s sm al l in wid thNo ne Pad has no pa t te rnCirc le Pad has a round l ine(s )Ova l Pad has an ova l l ine(s )Horizonta_ l ine Pad has a horizo ntal l ine(s)2 k inds Pad has 2 k inds of l ine

~ . ! ~ ' . 4 m NvM~/lfft~

r 'aa area is LargePad area i s meo ium

Sm al l Pad a r ea i s sma l l

Sharp chevront i en t t e chev ronI r regular chevron

Uppe r edge ha s a sm a l l rad iu s o f cu rva tu r eupp e r e a~e ha s a l a rge raom s o t cu rva tu r eUppe r ed~e ha s an i r regu l a r shape

Th e pa t te rns to be recogn ized in th i s wo rk were i llus t ra tions of car s teer ing whee ls . S ince

i t wa s a s su me d t ha t f r e ehand i l l u st r a ti ons wou ld be i nc luded , i t wou ld be im poss ib l e t o avo id

d i sp l ace m en t o r changes . An e f fo r t was mad e to dev i s e an e ff ec t i ve w ay o f ove rcom ing t h i s

problem . Th e metho d adopted here f i r st reso lves the ind iv idua l pa t te rns tha t a re in te rconnec ted

wi th in an im age in to cons t i tuent l ines . Then , these l ines a re in te rpre ted on the b as i s of in t rins ic



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kno wledg e o f each l ine assumed to be present in a s teering wheel im age, and that facil i tatesrecognition of the design features.

Figu re 1 is a flow cha rt of the design feature recognition process beg inning with the inpu tof a steering wh eel illustration. Th e input illustration is first processed to obtain fine lines, and

line searches are then performed in order to resolve the image into its constituent lines. This

m akes i t possible to obtain feature information on each l ine. Using the information thus

obtained, a judg m ent is mad e as to whether the input image has been rotated.

If it is judg ed to have been rotated, the original imag e is displayed again an d m odified to

reflect the rotat ion. Follow ing this correction, fine-l ine processing , line searche s and

acquisition of feature information are performed again to facilitate recognition of the design

features. The results are then output for display on a comp uter screen.

(I n p u t steering wheel illustration )

I P e o m f m e - l m e - o o s s i n g I

Perform line search to obtainfeature information

Procedure when orig inal image ha s been rotated

~ , , on,~.g.y~~lnfifiOgeO?f~ ~ Disp lay original image again I

P r f~ _ ~ [ e orm correction for rotation ofI N o I o g i n a g e

[ P e r f o r m free line processing 1

[ Recognition of steering ] Perform line L h to obtain ]wh eel design features ~ feature information

IOu tput recogn ition results I

Fig . l .F low chart o f des ign fea ture recogni t ion p rocedu re

2.1 Algo ri thm for design feature recogni t ion

An explanation is given here of the recognition algorithm for a case where the original

imag e has n ot been rotated. The line-search operation resolves the illustration into several lines,

and featur e inform ation is obtained on each line. At this point, it is nec essary to interpret

precisely wh at each line is, in order to support recognition o f the design features o f the steering

wheel. The lines presumed to make up a steering wheel image can be divided into three major

types: back grou nd portions, the pad surface pattern or horn portion and the bou nda ry lines

betw een the pad and the spokes. Specific exam ples of these l ines are shown in Fig. 2.

Rec ogn ition o f these three types is performed in a series of operations at different levels usingintrinsic know ledge regarding the area of each type.



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t ~ e r i n ~ w h e e l i m a g e L e v e l 1

0 0

F i g . 2 . R e s o l u t i o n o f s te e r i n g w h e e l i m a g e i n t o c o n s t i t u e n t l i n e s

Based on the resul t s thus obta ined , the process of recogniz ing des ign fea tures proceeds

accord ing to the des ign e lements and ca tegor ies shown in Tab le 1 . An exp lana t ion o f the

procedure i s g iven be low.

1 . Calcu la t ions a re mad e of the center poin t of a l l the lines indica ted a t leve l 2 and o f the

distance from the center point of the l ine denoted as (1) in Fig. 3.

2 . Us ing in t rins ic knowledge about d i st ance, a de te rmina t ion i s made as to whethe r the objec t

line is a candidate l ine for the horn portion.

3. U sing int r insic know ledge ab out dis tance and temp late matching, a determinat ion is m ade as

to wh ether the object l ine is par t of the pad surface pat tem.

4 . Th e rem aining l ines tha t a re not par t of the horn por t ion or the pad sur face p a t t e rn a rechan ged to those indicated at level 3.

5. A ll the l ines at level 3 are cleared from the screen.

6 . Us ing the backgroun d por t ions a t leve l 1 , the number of spokes i s counted .

De pend ing on the num ber of spokes present, the subsequent procedure o f the recogni t ion

a lgor i thm ch anges s l ight ly . The fo l lowing explana t ion i s for a s teer ing wheel sam ple having

f ou r s pokes .

7. Th e heigh t of the pad is determined from the center points of lines (2) and (4) in Fig. 3.

8. Th e width of the pad is determined from the center points of l ines (3) and (5) .

9. Th e are a of the pad is determined from the area of lines (1), (2) , (3) , (4) and (5) .



( 1 )0 . T h e s i z e o f t h e s p o k e a n g l e is

de te rmined f rom the d i f fe rence be tween the

poin t w here the v er t ica l ax is f rom the center

o f ( 1 ) c ro s se s ( 2 ) and t he l owes t po in t o f

the vert ical axis of (2) .11 . The sha pe o f t he pad ' s uppe r edge i s

de t e rmined f rom the s iz e o f t he spoke ang l e

and a shape search per formed on l ine (2) .

12 . The d i s t inc t i on be tween open space

e m p h a s i s o r s p o k e e m p h a s i s i s b a s e d o n a

ru le tha t a l l four -spoke s teer ing wheels a re

o f t he t ype t ha t a ccen t s t he shapes o f t he

open spaces .

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( 5 )

F i g . 3 . N u m b e r s o f s t e e r i n g w h e e l l in e s

2 . 2 R e c o g n i t i o n r e s u l t s f o r s t e e r i n g w h e e l i l lu s t r a t i o n s

The above -men t ioned a lgo r i t hm was i nco rpo ra t ed i n to a de s ign f ea tu r e c l a s s i f i c a t i on

sys t em . I l l u s tr a t i ons o f s t e e ri ng whee l s am p le s we re i npu t in to t he sy s t em and a r ecogn i t i on

t e s t o f the de s ign f ea tu r es was conduc t ed . Typ i ca l r e su lt s ob ta ined a r e shown in F ig . 4 . As

indica ted in th i s figure , the sys tem i s capable of d i sp lay ing an im age o f an input i l lus t ra tion and

the ca tegor ies recognized for each des ign element.

N o. o f s po ke s * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *P a d h e i g h t * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *a rge

P ad w id th * * * * * * * * * * * * * * * * * * * * * * * * * * * * e di umP ad a re a * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *a rgeS p o k e a n g l e * * * * * * * * * * * * * * * * * * * * * * * * * * * * *a rgeShape o f pad uppe r edge * Chev ron w i th i r r egu la r shapeS iz e o f s id e o pe n s pa c e * * * * * * * * * * * * * * * * * * * * m a l lO p e n s p a ce e m p h a s i s o r s p o k e em p h a s i s * * * * * * * * * * * *• * * * * * * * * * * * * * * * * * * * * * * * * * p e n s pa ce e m p h as isP ad su rfa ce p atte rn * * * * * * * * * * * * * * * * * * * * * * * * * * * * *• * * * * * * * * * * * * *Oval pa t te rn and two ho r izonta l l inesH o r n p o sit io n * * * * * * * * * * * * * * *E m b e d d e d i n s p o k es

F i g . 4 . T y p i c a l r e c o g n i t i o n r e s u l t s f o r s t e e r i n g w h e e l i l lu s t r a t i o n

The sys t em cou ld no t r e cogn i ze such de s ign e l emen t s a s t he p r e sence o f f i nge r r e s t s ,

con t i nu i t y be tw een t he spokes and t he pad and t he p r e sence o f con t ro l sw i t ches , a s i t was

d i f f icu l t to con f i rm de f in it e i n fo rma t ion on t he se e l emen t s . W i th t he excep t i on o f the se t h r ee

e lem ents , i t recognized 90% of the des ign fea tures of the 30 s teering wh eel sam ples .

The samples for which fea ture recogni t ion was not poss ib le or recogni t ion e r rors occur red

tended to have a co m plex cont ro l sw i tch layout or in t r ica te boundary l ines .

3 . C O N C L U S I O N A N D F U T U R E P R O S P E C T S

I n t h i s r e sea r ch , image r ecogn i t i on t e chno logy was app l i ed t o t he au tomot ive s t e e r i ng

whee l w i th t he a im o f a ch i ev ing ob j ec t i v i t y i n t he c l a s s i f i c a t i on o f t he phys i ca l f e a tu r e s o f



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products in the discipline of kansei engineering. An autom atic feature classification system w as

developed that showed a high rate of accurate recognition of the limited samples (i.e.,

illustrations) used in this stud y, w ith the exception of som e physical features. Recogn ition test

results confirmed that this system has the potential for use in the automatic recognition of

physical features in the kansei engineering field.The re are still m any issues that mu st be resolved, however. On e issue concerning the

presen t recognition system for steering w heel design features is to ach ieve a higher rate of

recognition and the capability of recognizing the design elements that the system failed to

recognize in this stud y. Th is will require further refinement of the recognition algorithm and the

application o f mo re advanced image recognition technology. An other issue is to achieve

recognition of design elements based on photographs and other visual images in addition to

illustrations.

In order to recognize the design features of steering wheels from photographs of car

interiors, it is necessary to isolate the steering wheel from the instrument panel and dashboard

that form the backgrou nd. T hi s is especially difficult to accomplish in the case of car interiorsamples photographed under nonuniform conditions due to shad ows created by light coming inthrough the windshield. The authors intend to pursue the possibility of accom plishing the

second issue using samples photographed under certain given conditions, instead of a large

num ber o f unspecified samples.

Once the second issue has been accomplished, it should be technically possible to

discriminate the shape and other phy sical features not only of the steering w heel but also of the

instrum ent panel and dashboard from photographs of car interiors. The autho rs intend to

pursue the development of technology for automatically recognizing the design features of the

entire car interior, and incorporate the data obtained into a kansei engineering system for

estimating the o verall imp ression convey ed by a car interior design.

R E F E R E N C E

1. T.Jindo and K.Hirasago, A Study of Kansei Engineering of Passenger Cars, Proc' of

JAPA N-U .S.A. Sym posium on Flexible automation(1994).

2. T.Jindo and K .Hirasago, The Developm ent of Car Interior Imag e System Inco rporating

Know ledge Engineering and Com puter Graphics, Proc. of IEA, 625/627 (1991).

3. M.Nagamachi, Development of Interior Consultation Sys tem using Know ledge

Engineering Method, The Japanese Journal of Ergonomics V ol.22, No.1,1/7(1986).

4. G.Strang,Wavelets and Dilation Equations, SIA M Review, V ol.31,No.4, 614/627(1989).5. T.Yanagishima and M .Nagamachi, Kansei Engineering Approach to A utomobile Interior,

The Japanese Jornal of Ergonomics Vol.24, No.6,38/40(1988).

6. T.Nishimura and T.huzimoto, Fast Co ntour Line Extraction A lgorithm Selectively Using

Threshold V alues Observing Line Connectedness, The Transactions of the Institute of

Electronics, Information and Communication Engineers, Vol.J76-D-II, No.6,

1186/1193(1993).

7. T.Watanabe and T.Shibata, Detection o f Broken Ellipses by the H ough Transforms and

M ultiresolutional Ima ges, The T ransactions of the Institute of Electronics, Information

and Com munication Engineers, Vol.J73-D-II, No.2 , 159/166(1990).

8. Y.Hotta, M .Miyahara and T.O take, Reg ion Segmentation Image Coding Using the LocalFeature of Color Inform ation, The T ransactions of the Institute of Electronics,

Information and Communication Engineers, VoI.J76-D-II, No.5, 1023/1037(1993).

A Study of Image Recognition on Kansei Engineering

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