that's one um i um is and the a pair of uh uh but subject to change are but the some about uh the more it's yeah for true yeah also maybe some things about uh the uh modeling issues i start i want to go through a very quickly through the enjoyment you have an image by which the what we call excel uh they stay on a i i is it two a is and do can excel as that was sent there's a that time was you see you know uh that or noted the U are two a so are such as so and our goal is to uh are present the contour of a each you go by image it has but use for while zeros model and that the ones are yeah for that foreground this zero a the debate the court would stay in between the for foreground and background if by to be contained in the foreground the cells not to you want to be three for you see there for mean required for binary image they have the property that uh uh they have an a part which is on the big so a the so from the for a each has an they work on them the ground would be a don't to the core uh the the a being counted he you know for one it so what we can see that the a binary in each and the contour for are or we in the same information they can be a no one one mapping whatever you have one we can you i the other as well so called or more in a binary image is you to call or modeling a whole yeah going to a first of one for the sequence of big sense you one N each chi a a a it's so for an A the would be given mentioned like T and a property P of this change of excess would be that to uh and and pair can see that you the it sense would be connected in eight i or are for the creation uh which you have been yeah that is that and the court it's of the next uh uh so in the for it's of the last but i G placement which are a a lot of be in as one one set except they uh but zero zero so we don't allow here instead so to state a things we have always move a but i right all the directions right and north so it that that are not R no you if we look at all these past what three uh movements months on one for we can see that a uh we can buy eyes this very is you by a number you which has a they use from zero to seven and the equation the to get the court it i G from uh you think about a phrase a number of you would be but i mean the course i i times that that five or four times and the same uh that for sinus you of the or the G and you we have that dog so now we make all these uh a was a kid eva uh mark was of five or for they are going to get the allowed oh zero would be for for well be back don't uh down works uh then two but what or and so on so all of these are allowed but and this a ah a prioritisation uh it does uh introduced in that this segment is the a few it can be cheap which uh uh so that the we have a part their that's zero seven and uh our final change own would be a sequence of those that but don't numbers can be a uniquely defined by is you quality so if we take a job you got uh one issues of the pixels but that's lot i T we get the i i to me at time a a a a that is a very simple because uh fashion to get the job but you presentation based on that uh on there a now we can component that we have a but of the point by you the first position of the so say i'm core chain and then a sequence of a simple the change sequence is now be in this set zero you know seven and that would be no one one correspondence to the gym you can sequence of excess P you want to P M no i was observed that the uh uh this uh uh a few might quotes are would be to D dot then and it's much more a efficient two introduce a new variable called the bit at T might as well when the and cold but actually D uh a my simple so we have but minds the might as well that would be we that is like we take a is operation uh we but as the model at uh subsection and they they the non-negative in is a uh now we see that uh these new numbers be tough uh are also connected to the positions because of each other but your are uh called binary T and in fact is that there is a very simple and nice the passion for getting the positions of pieces the second point you the position of the peaks the previous time and the uh next to used in the box and are new i'm then be thirty which is the partition you you might change where these metrics is that methods similar so now i mean that a a second uh it really representation of V C of pixels that the position of the first six and what addition of the second um and then we have that uh a chain code you can be numbers in this said the uh okay and it's in being model they we have a number this at zero one up seven yeah is um uh to code we you discuss a now it would you a are you to be seven that was that B point where you have to move as you see they are a a when T V D so we move sometimes that all like here sometimes because sometimes okay that but it is what well as uh it's so wise it i Y way to represent the binary make but there is also a lot and i think we how to we presented the the by introducing yeah and S got that P which are packages are is are to those so they are got three use the back is these be uh that this is of those at so we can uh uh also discuss about the chain codes are representations or water just like it is that is to now we have been in the this that this points you want to and so on if we translate the that is by a step vertically and horizontally we are going to get a like things and we can discuss about change "'cause" when this describe that but is interesting is that now we have to move just in for what a T V so this uh but this is i mean to provide a something in for it but and the um we see that the uh length of the joint code here would be use a number member and we went much longer than the change a the peaks do have just seven except the J you would have sixteen now the question is which would be the best presentation which one should be used for encoding uh the same P and and T which is the one of the age that it is and exactly the same information so we have to use uh which are better use the best is result a discussing about was so uh but that uh a chain codes we can do to this exactly as before uh that female chain code in the uh what if D V D for where you have a a very similar to the definition as a for now this numbers almost a a in this a zero one two three that just for values for grammar and uh our what the image you would be no if we want and uh two D set the initial that X plus the yeah my one uh points from the uh a change words on the task with that we can two also of attention uh codes by introducing these difference between galactic that one runs on that would believe that it is gonna before that is for this is that uh uh it is that is that is not just think that i whole which is quite a few O T are introduced there later than well yeah that's is is that to the fast at the uh you uh of you well but not it's not as we had before yeah for for that a definition my code we had the difference between two uh you my quotes you these and you had that second order then memory now we don't have any more a second order memory more in fact we have a model with the uh you put a very long memory uh because now introduce to state variables which i we to tell if the sense of a movement or along the horizontal vertical direction uh i get or not so he's are state that that would be to state tiger was and the code itself would be defined as uh is you know in that is no change direction why if there is a change that but but you that well sense whatever whatever moved that direction and the call to would be one you change point detection and the sense no that direction so this would be a very uh lot of memory of the nation and i for now we had a have to say but and what of be chain code then what is the next that that's in the chain of and sequence of your these uh yeah a representation for is very simple going to with that we have the corporate along that the they sounds there thirty seven cents and the colours are in the set that zero one to up to seven and and you have also the called uh a i the got yeah images and you see this sequence of uh simple in the a a T a but as you one and two uh we have a much more C press of that this is a you T all of them combat to thirty seven except and that may say that probably this is less efficient cool but is not and right as in is that uh we have a few force what but they are just zero one and two but a more uh uh what is more interesting is that the simple to we you know change direction and sense but you is that we sell them in the scene so basically they we we have to see then it to see what it should get most of the time and uh this would be a but it should be able what would be to for uh why we are to see this this the compression problem uh uh because the uh you may want think one by reading is and then would be important so but may also can here a very good statistical models object we can call this features objects for a a recognition and main wants to know what is the minimum description length for uh this models so for that reason we are interested in the most that's compression of the contours and that's who the study with need in this the they well so there is not but um which is but yeah well what did but is not identical is that notation contours in image segmentation and image segmentation also a very important the uh a region and you do we need other you what is the state of that the of corporation of four chain codes uh how how a codes have been used to the twenty years ago um they are a fixed uh codes defining a simple was for the for a the extensions for who but that was uh used the five years ago a a able to variable able uh coding run it's building that also use uh a what was used in a very nice paper in two thousand six but the recognition was uh a or text these for this code the you might and that was used for map uh what of mess they have a C are they are they specific or uh a lot of this i i think of it to um conflicting here a results not i is this is it telling you should use this uh uh them a the back pages follow like to publish and you what the best these definition if a code the conclusion in this paper would be that this is not the best is second best but the the best but would be in that a a three T which is more that's one reason why it was not start it so well not so the question would be what is the best the should should more than four or the modeling we that was something in important this type conditional probabilities what would be that the probability of the key even all that D the previous moment and we have the same for big so and here for but so our goal is to a which of these is that better suited for our one want to a a uh i our um first for the second are model we we have just introduced at these few my codes and iteration not well but in our paper but we are we can get also a a higher order models what you combine these first order and second order models uh in uh my model so memory a which use a fixed but next memory or or you models where the memory of the model depends on a so we have a or or just uh compressing a the point two for is the that's pretty oh time series is then we product working to you should use in the decoding and have a this is a um need to um is that three where we have a on the route or one on the nodes the nodes we have deviations oh we have to an estimate notes that was a channel uh they can either or distribution that was which are thirteen they are used ooh when whenever code so we joined the distribution quality these note now when it would coding in a lot of this court so this kind of a a context you recorded data we context the i i assume is not uh what did you are but they do find and you that of the digital uh a a a a base the T but uh not is pulling it was less uh uh uh use how they it the the the coding is that paper mission by a a over and the from used for depression my a a big problem of be how to optimize the point T structure and we have but class of that i a problem uh for choosing this uh structure of the T that's any one context you which is four uh symbols in the previous positions in the G um we put that the statistics of of of of the counts we do i'd made in here so well the time we collect at the T V what would the code lengths at time T but the index but that's in that's and uh we are it mostly in the find a a a a a get to the and the of the the sequence get that and uh uh are study after we get to the at least i be at each node what we what is the balance between coding don't coding to the choose we just at the codes of the children or back to the bottom you for be a a part and is uh next year is that than the children last a T uh because you have to encode the structure of this uh a those relations and whenever a this happens uh we you this you know as and that you node otherwise it would be a as a uh i and we provide like data five or or for this next uh politicians these calls that is that i think that um that and program a way to optimized the quantity structure now we've the putting we have a a bit more did you got or more more thinks to study we um like the statistics not only that the note to and time T well so we take all the possible groupings of E children a second no and and a complete the such a a a code oh that is because the same so choosing which two to use would be the uh a a class the lucky which is now we can do that uh structure of the three so that is a a set to me a a a a are adapted the a we encode first thing for the structure of the T we number that is the best the at and of our change all and then we just we that uh chain code the with a i keep statistics but this that no no a or two show some results but that we have this a set of the what high by use only when B are shown here that a very different from you you know like to make it to you know but a a some images is making many holes uh i think you're going we can everything think there which uh would be equivalent to a won't the full binary one example is this uh a set in each and you can see what is that the optimal structure of the P for a uh you T change go and that would be to what the most structure forty uh to finish if you michael this uh uh uh if it should if you might what would have just a five song the for i simple this one seven something to hide that the structure of the fee is you more interesting if you represent dramatically what would be a to "'cause" that these of this call you we have the context what do with the excel you have the context text up with a a a guy it is and you that the german because sectors are no longer for the crack them for the because although the two are it but and representation the context and this statistical on uh a it's to and S is different in the two representation maybe i'm going the desired yeah the results for the one having five we had in the that sense yeah a and we uh it represents in um course or the performance of the and probably by a context C everything here we different from the a chain codes the that really to be as your T which is the bands well yeah or so that would be the zero line oh yeah as is that you can see a higher on top of these you don't my meaning that they are not as efficient as the code you want the and that happens for all the five the best company but is still on the uh yeah a is the core the a a month with this neighbour for uh and then um blue um is there uh the best the context the on T D excel one is a that that was a is i it's of a a code by grouping i this is that the the sure that is that that's which are published in a recent paper in uh at yeah just of that since the processing but that is as well as you can see here i results in the context you at what is the i a much better a tens of course and a a better than then the this one uh here what they use that you just at a few or more more and they established by a uh yeah you great again that the best legs for all the models would be be well as we have a uh due to a possibility to take the longest uh one text and the were used other markov model and we you got but but a result for or T one hundred five and for each individual files or is that a special but is day uh dependence of the possible and that's so be um models and as you see uh our T models such a some points so at this point you may say that this they what they're six get the best performance uh a of the models so this the same that additional it happens us by the same or the same plane as got images we have many presentations ah a a of the contour data are uh we found that a statistical efficiency of in E papers right but change and the uh when we have when we use uh a T context modeling for a uh that is a significant difference between the trees for one in which what D image so for that we said that but that we use in adaptive but for uh i think of and what we see find it that the what we we won't and is not only yeah uh important point coding but is also for a find good this kid of uh binary images i you the i i i i have time to ask some session for for a i yeah i ask i that's i yeah about